{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"mount_file_id":"1Bhc3hl9L9UxbEQbBAZy87fYeLrHGpdiO","authorship_tag":"ABX9TyNteQCi4IWJlS6F1KrYD4xS"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["### Импортируйте все необходимые библиотеки."],"metadata":{"id":"RNWxsuPljnvZ"}},{"cell_type":"code","execution_count":118,"metadata":{"id":"uAVZtxn4hS-M","executionInfo":{"status":"ok","timestamp":1719734442140,"user_tz":-180,"elapsed":328,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"outputs":[],"source":["import keras\n","from keras.layers import *\n","import matplotlib.pyplot as plt\n","import numpy as np\n","import keras.utils\n","from random import randint\n","import pandas as pd\n","from keras.utils import to_categorical\n","from keras.models import Sequential\n","from keras.layers import Dense, Flatten, Input, Conv2D, MaxPooling2D, Dropout, AveragePooling2D"]},{"cell_type":"markdown","source":["### Загрузите из keras.datasets набор данных fahion_mnist."],"metadata":{"id":"SjJKyeOjJRoL"}},{"cell_type":"code","source":["(x_train, y_train), (x_test, y_test) = keras.datasets.fashion_mnist.load_data()"],"metadata":{"id":"b14_2iCnhr9d","executionInfo":{"status":"ok","timestamp":1719734444032,"user_tz":-180,"elapsed":384,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":119,"outputs":[]},{"cell_type":"markdown","source":["### Ознакомьтесь с данными, используя различные методы. Сделайте выводы об этом наборе данных."],"metadata":{"id":"yoEpiHB0JZ7J"}},{"cell_type":"code","source":["# Проверим тип данных\n","print(type(x_train))\n","print(type(y_train))\n","print(type(x_test))\n","print(type(y_test))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"mGetnPxDJf46","executionInfo":{"status":"ok","timestamp":1719734445250,"user_tz":-180,"elapsed":5,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"b8c5e596-342d-41d9-be97-f0035a0d9367"},"execution_count":120,"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'numpy.ndarray'>\n","<class 'numpy.ndarray'>\n","<class 'numpy.ndarray'>\n","<class 'numpy.ndarray'>\n"]}]},{"cell_type":"code","source":["# Отобразим форму массивов\n","print(x_train.shape, \" - набор для обучения\")\n","print(y_train.shape, \" - лейблы для обучения\")\n","print(x_test.shape, \"- набор для тестов\")\n","print(y_test.shape, \" - лейблы для тестов\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"8xXqkNjdoaZW","executionInfo":{"status":"ok","timestamp":1719734447000,"user_tz":-180,"elapsed":5,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"38f086f1-c5b2-4898-bcbe-9c0eeb35ea56"},"execution_count":121,"outputs":[{"output_type":"stream","name":"stdout","text":["(60000, 28, 28)  - набор для обучения\n","(60000,)  - лейблы для обучения\n","(10000, 28, 28) - набор для тестов\n","(10000,)  - лейблы для тестов\n"]}]},{"cell_type":"markdown","source":["**Вывод 1**  \n","* Набор данных содержит 60 000 изображений размером 28x28 пикселей для обучения модели и 10 000 аналогичных изображений для тестирования (в общей сложности 70 000 изображений).  \n","* Данные обучения представлены в виде многомерного массива NumPy, а метки - в виде одномерного массива.  "],"metadata":{"id":"Odwe6och-B4f"}},{"cell_type":"code","source":["# Выведем значения меток\n","labels_list = sorted(set(y_train))\n","labels_list"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"YROoN1qB73l_","executionInfo":{"status":"ok","timestamp":1719734449660,"user_tz":-180,"elapsed":303,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"d46ddace-43dc-49b8-d605-4cab7c56a12d"},"execution_count":122,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]"]},"metadata":{},"execution_count":122}]},{"cell_type":"markdown","source":["**Вывод 2**  \n","Набор данных содержит 10 классов с лейблами от 0 до 9"],"metadata":{"id":"1goPBRUL8I2Q"}},{"cell_type":"code","source":["# Выведем минимальные и максимальные значения\n","print(np.min(x_train),\" - \", np.max(x_train))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"yj7u0h65o9gT","executionInfo":{"status":"ok","timestamp":1719734452051,"user_tz":-180,"elapsed":361,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"ca220b77-6c15-4e32-bff8-e3727eef304d"},"execution_count":123,"outputs":[{"output_type":"stream","name":"stdout","text":["0  -  255\n"]}]},{"cell_type":"markdown","source":["**Вывод 3**  \n","Набор данных содержит значения от 0 до 255. В дальнейшем эти значения необходимо преобразовать в значения от 0 до 1"],"metadata":{"id":"oxf2I2nhynEm"}},{"cell_type":"code","source":["# Проверка распределения классов в тренировочных данных\n","unique, counts = np.unique(y_train, return_counts=True)\n","class_distribution = dict(zip(unique, counts))\n","\n","print(\"Распределение классов в тренировочных данных:\")\n","for class_label, count in class_distribution.items():\n","    print(f\"Класс {class_label}: {count} примеров\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"BgEvqiiI9UHU","executionInfo":{"status":"ok","timestamp":1719734454961,"user_tz":-180,"elapsed":382,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"99ec54e2-0409-47a1-ed7c-39dc666a9a10"},"execution_count":124,"outputs":[{"output_type":"stream","name":"stdout","text":["Распределение классов в тренировочных данных:\n","Класс 0: 6000 примеров\n","Класс 1: 6000 примеров\n","Класс 2: 6000 примеров\n","Класс 3: 6000 примеров\n","Класс 4: 6000 примеров\n","Класс 5: 6000 примеров\n","Класс 6: 6000 примеров\n","Класс 7: 6000 примеров\n","Класс 8: 6000 примеров\n","Класс 9: 6000 примеров\n"]}]},{"cell_type":"code","source":["plt.figure(figsize=(10, 5))\n","plt.bar(class_distribution.keys(), class_distribution.values(),\n","        tick_label=[f\"Класс {i}\" for i in class_distribution.keys()])\n","plt.xlabel(\"Класс\")\n","plt.ylabel(\"Количество изображений\")\n","plt.title(\"Грыфик распределения классов\")\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":487},"id":"qRINEgCM_u16","executionInfo":{"status":"ok","timestamp":1719734456924,"user_tz":-180,"elapsed":408,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"b63441bc-0e87-48b4-de79-44cfd79d765c"},"execution_count":125,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x500 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["**Вывод 4**  \n","В наборе данных для обучения - данные распределены равномерно"],"metadata":{"id":"QBI-D6JpAbCp"}},{"cell_type":"markdown","source":["### Проверьте набор данных на наличие пропусков и дубликатов"],"metadata":{"id":"AHZAL2okANyx"}},{"cell_type":"markdown","source":["Для этой проверки я буду использовать Pandas, так как он мне более привычен. Для этого необходимо преобразовать набор данных в одномерный массив и изменить его тип с numpy.ndarray на pandas.DataFrame."],"metadata":{"id":"cKm_N8XmdfPZ"}},{"cell_type":"code","source":["x_train_2d = x_train.reshape((60000, 28 * 28))\n","x_train_df = pd.DataFrame(x_train_2d)\n","\n","x_test_2d = x_test.reshape((10000, 28 * 28))\n","x_test_df = pd.DataFrame(x_train_2d)"],"metadata":{"id":"1nG9fBBGw9TV","executionInfo":{"status":"ok","timestamp":1719734461332,"user_tz":-180,"elapsed":303,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":126,"outputs":[]},{"cell_type":"code","source":["# Отобразим случайные строки из датафреймов для проверки\n","print(x_train_df.sample(1), \"\\n----------------------------------------\")\n","print(x_test_df.sample(1))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"6JEJmAFcyl-t","executionInfo":{"status":"ok","timestamp":1719734463498,"user_tz":-180,"elapsed":324,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"0b3d2267-11aa-4f67-f52d-a887b42177e1"},"execution_count":127,"outputs":[{"output_type":"stream","name":"stdout","text":["       0    1    2    3    4    5    6    7    8    9    ...  774  775  776  \\\n","11238    0    0    0    0    0    0    0    0    0    0  ...    0    0    0   \n","\n","       777  778  779  780  781  782  783  \n","11238    0    0    0    0    0    0    0  \n","\n","[1 rows x 784 columns] \n","----------------------------------------\n","       0    1    2    3    4    5    6    7    8    9    ...  774  775  776  \\\n","44057    0    0    0    0    0    0    0    0    0    0  ...    0    0    0   \n","\n","       777  778  779  780  781  782  783  \n","44057    0    0    0    0    0    0    0  \n","\n","[1 rows x 784 columns]\n"]}]},{"cell_type":"markdown","source":["Для меток преобразование не требуется."],"metadata":{"id":"kwXDr3Ucx-p9"}},{"cell_type":"code","source":["y_train_df = pd.DataFrame(y_train)\n","y_test_df = pd.DataFrame(y_test)"],"metadata":{"id":"zwTcroUKw91M","executionInfo":{"status":"ok","timestamp":1719734465900,"user_tz":-180,"elapsed":313,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":128,"outputs":[]},{"cell_type":"code","source":["# Отобразим случайные строки из датафреймов для проверки\n","print(y_train_df.sample(1), \"\\n----------------------------------------\")\n","print(y_test_df.sample(1))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"WIblJeSO01B1","executionInfo":{"status":"ok","timestamp":1719734468069,"user_tz":-180,"elapsed":305,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"be1a2f47-8b11-4416-b2f2-c43f58f31588"},"execution_count":129,"outputs":[{"output_type":"stream","name":"stdout","text":["       0\n","29155  4 \n","----------------------------------------\n","      0\n","9335  5\n"]}]},{"cell_type":"markdown","source":["Проверим набор на наличие пропусков."],"metadata":{"id":"PRgVFCvj0JjH"}},{"cell_type":"code","source":["# Функция проверки наличия пропусков\n","def find_skip_data(df):\n","    skips = df.isnull().sum()\n","    skipping_columns = skips[skips > 0].index.tolist()\n","\n","    skips_count = len(skipping_columns)\n","    if skips_count > 0:\n","        print(f\"Обнаружено колонок с пропусками: {skips_count}\")\n","        print(\"Колонки с пропусками и количество пропусков в них:\")\n","        for column in skipping_columns:\n","            print(f\"{column}: {skips[column]}\")\n","    else:\n","        print(\"Пропусков НЕТ!\")"],"metadata":{"id":"W6RRDqZP7mmt","executionInfo":{"status":"ok","timestamp":1719734470440,"user_tz":-180,"elapsed":330,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":130,"outputs":[]},{"cell_type":"code","source":["find_skip_data(x_train_df)\n","find_skip_data(y_train_df)\n","find_skip_data(x_test_df)\n","find_skip_data(y_test_df)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"fpi5wCOT5Fyo","executionInfo":{"status":"ok","timestamp":1719734472598,"user_tz":-180,"elapsed":308,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"f7e71ccd-3aaa-438f-f874-1de19e70aeac"},"execution_count":131,"outputs":[{"output_type":"stream","name":"stdout","text":["Пропусков НЕТ!\n","Пропусков НЕТ!\n","Пропусков НЕТ!\n","Пропусков НЕТ!\n"]}]},{"cell_type":"markdown","source":["Проверим набор на наличие дубликатов."],"metadata":{"id":"0WFe43Ux4dyh"}},{"cell_type":"code","source":["# Функция проверки наличия дубликатов\n","def find_duplicates(df):\n","    duplicates = df.duplicated().sum()\n","    if duplicates > 0:\n","        print(f\"Количество дубликатов: {duplicates}\")\n","    else:\n","        print(\"Дубликатов не найдено\")"],"metadata":{"id":"FOZ7x1shA3Wm","executionInfo":{"status":"ok","timestamp":1719734474350,"user_tz":-180,"elapsed":341,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":132,"outputs":[]},{"cell_type":"code","source":["find_duplicates(x_train_df)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cylsTY5OBFDN","executionInfo":{"status":"ok","timestamp":1719734479393,"user_tz":-180,"elapsed":2817,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"851b5d2f-5afd-419c-8bda-4b13e38885c2"},"execution_count":133,"outputs":[{"output_type":"stream","name":"stdout","text":["Дубликатов не найдено\n"]}]},{"cell_type":"code","source":["find_duplicates(x_test_df)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"p1tUq79SBA0M","executionInfo":{"status":"ok","timestamp":1719734483304,"user_tz":-180,"elapsed":2259,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"68657677-5978-4b8b-909d-c77b7bfd04aa"},"execution_count":134,"outputs":[{"output_type":"stream","name":"stdout","text":["Дубликатов не найдено\n"]}]},{"cell_type":"markdown","source":["Дополнительно, хочу проверить, совпадает ли длина массивов меток и изображений"],"metadata":{"id":"RSsR353-FTZS"}},{"cell_type":"code","source":["# Проверка равенства длины массивов\n","assert len(x_train) == len(y_train)\n","assert len(x_test) == len(y_test)"],"metadata":{"id":"7rv1E0woDk7A","executionInfo":{"status":"ok","timestamp":1719734484479,"user_tz":-180,"elapsed":4,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":135,"outputs":[]},{"cell_type":"markdown","source":["### Отрисуйте первые десять примеров с метками классов."],"metadata":{"id":"5wyzg9FoOoXy"}},{"cell_type":"code","source":["fig, axes = plt.subplots(1, 10, figsize=(10, 10))\n","\n","for i, ax in enumerate(axes):\n","    ax.imshow(x_train[i], cmap=plt.cm.binary)\n","    ax.set_title(y_train[i])\n","    ax.axis('off')\n","\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":125},"id":"Z_J0vQ8oOILr","executionInfo":{"status":"ok","timestamp":1719734487630,"user_tz":-180,"elapsed":1234,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"f870feec-5148-4999-c7ca-142acd849dae"},"execution_count":136,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x1000 with 10 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["Дополнительно, хочу вывести по одному изображению для каждой метки"],"metadata":{"id":"Q-PJWw-QO1O6"}},{"cell_type":"code","source":["samples_per_class = {}\n","\n","for i, l in zip(x_train, y_train):\n","    if l not in samples_per_class:\n","        samples_per_class[l] = i\n","        if len(samples_per_class) == len(labels_list):\n","            break\n","\n","fig, axes = plt.subplots(1, len(labels_list), figsize=(10, 10))\n","\n","for class_idx, (label, image) in enumerate(samples_per_class.items()):\n","    axes[class_idx].imshow(image, cmap=plt.cm.binary)\n","    axes[class_idx].set_title(label)\n","    axes[class_idx].axis('off')\n","\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":125},"id":"4kJaSW2jTehB","executionInfo":{"status":"ok","timestamp":1719734490727,"user_tz":-180,"elapsed":920,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"f89e3f28-335a-4538-cd53-716969677f2b"},"execution_count":137,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x1000 with 10 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["**Вывод 5**  \n","Теперь мы можем определить, какая одежда соответствует каким меткам.\n","0. Футболка / топ\n","0. Брюки\n","0. Пуловеры\n","0. Платье\n","0. Пальто\n","0. Сандалии\n","0. Рубашка\n","0. Кроссовки\n","0. Сумка\n","0. Ботильоны  \n","Признаться честно, я подсмотрел названия на GitHub :) Мои познания в моде, к сожалению, ограничены. Просто, это была интересная задача\n","\n"],"metadata":{"id":"Wa3adrRLAghr"}},{"cell_type":"markdown","source":["### Подумайте, как стоит преобразовать входные и выходные данные, чтобы нейронная сеть могла лучше с ними работать. Выполните эти преобразования."],"metadata":{"id":"VIhvw84WZLuN"}},{"cell_type":"markdown","source":["Для начала выполним нормализацию значений пикселей, преобразовав их в диапазон от 0 до 1."],"metadata":{"id":"qCR8rTVN7_Sf"}},{"cell_type":"code","source":["x_train = x_train / 255.0\n","x_test = x_test / 255.0"],"metadata":{"id":"FomUbtp93voX","executionInfo":{"status":"ok","timestamp":1719734495142,"user_tz":-180,"elapsed":298,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":138,"outputs":[]},{"cell_type":"code","source":["# Выведем случайное изображение после конвертации значений (для проверки)\n","random_cast = randint(0, x_train.shape[0])\n","plt.imshow(x_train[random_cast], cmap=plt.cm.binary)\n","print(y_train[random_cast], \"---\", random_cast)"],"metadata":{"id":"gh0az5UeIMgb","colab":{"base_uri":"https://localhost:8080/","height":447},"executionInfo":{"status":"ok","timestamp":1719734497087,"user_tz":-180,"elapsed":619,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"bce724c7-3925-45d0-fe08-b2f8516d79eb"},"execution_count":139,"outputs":[{"output_type":"stream","name":"stdout","text":["7 --- 7120\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"iVBORw0KGgoAAAANSUhEUgAAAaAAAAGdCAYAAABU0qcqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAdP0lEQVR4nO3df2xV9f3H8ddtodci7a2ltLeVwloU2ETqxqTrnAxHA3SJEeQPfyZgDEZWzJA5DYuCuiXdcHFGw3TJJmgi6lwEpoksWGyJs2BACSHTjtZOQGhRXO8thd4i/Xz/INx9rxThHO6977Y8H8lJuPee9z3vnp7eF+fe03cDzjknAADSLMO6AQDAxYkAAgCYIIAAACYIIACACQIIAGCCAAIAmCCAAAAmCCAAgIlh1g18XV9fnw4ePKicnBwFAgHrdgAAHjnn1NXVpZKSEmVknP08Z8AF0MGDB1VaWmrdBgDgAu3fv19jxow56+MDLoBycnIknWo8NzfXuBsAgFfRaFSlpaXx1/OzSVkArV69Wk888YTa29tVUVGhZ555RtOmTTtn3em33XJzcwkgABjEzvUxSkouQnj11Ve1bNkyrVy5Uh988IEqKio0e/ZsHT58OBWbAwAMQikJoCeffFKLFi3SXXfdpe985zt67rnnNGLECD3//POp2BwAYBBKegD19vZq586dqq6u/t9GMjJUXV2tpqamM9aPxWKKRqMJCwBg6Et6AH3xxRc6efKkioqKEu4vKipSe3v7GevX1dUpFArFF66AA4CLg/kvoi5fvlyRSCS+7N+/37olAEAaJP0quIKCAmVmZqqjoyPh/o6ODoXD4TPWDwaDCgaDyW4DADDAJf0MKCsrS1OnTlV9fX38vr6+PtXX16uqqirZmwMADFIp+T2gZcuWacGCBfr+97+vadOm6amnnlJ3d7fuuuuuVGwOADAIpSSAbrnlFn3++edasWKF2tvbdc0112jTpk1nXJgAALh4BZxzzrqJ/y8ajSoUCikSiTAJAQAGofN9HTe/Cg4AcHEigAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACACQIIAGCCAAIAmCCAAAAmCCAAgAkCCABgggACAJgggAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACACQIIAGCCAAIAmCCAAAAmCCAAgAkCCABgggACAJgggAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACACQIIAGCCAAIAmCCAAAAmCCAAgAkCCABgggACAJgggAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACACQIIAGCCAAIAmCCAAAAmCCAAgAkCCABgggACAJgggAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACAiaQH0KOPPqpAIJCwTJo0KdmbAQAMcsNS8aRXXXWV3n777f9tZFhKNgMAGMRSkgzDhg1TOBxOxVMDAIaIlHwGtHfvXpWUlKi8vFx33HGH9u3bd9Z1Y7GYotFowgIAGPqSHkCVlZVau3atNm3apGeffVZtbW26/vrr1dXV1e/6dXV1CoVC8aW0tDTZLQEABqCAc86lcgOdnZ0aN26cnnzySd19991nPB6LxRSLxeK3o9GoSktLFYlElJubm8rWAAApEI1GFQqFzvk6nvKrA/Ly8jRhwgS1tLT0+3gwGFQwGEx1GwCAASblvwd09OhRtba2qri4ONWbAgAMIkkPoAceeECNjY36z3/+o/fee0/z5s1TZmambrvttmRvCgAwiCX9LbgDBw7otttu05EjRzR69Gj96Ec/0rZt2zR69OhkbwoAMIglPYBeeeWVZD8lAGAIYhYcAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMDHMugEMXn19fWnZTkbGwP5/knPOc00gEEhBJ2d66623fNXl5OR4rhk2zPvLyaeffuq55siRI55rotGo5xpJys3N9VxTWFjouaa3t9dzzYgRIzzXSNLcuXN91aXCwP7JBgAMWQQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwwjBS++RkS6mdw58mTJz3XZGZmeq6RBvZg0RdeeMFzzVNPPeVrW5dffrnnms8++8xzjZ9hpH4GhGZnZ3uukaTOzk7PNX6OIT/7+/jx455rJKm8vNxzzZQpU3xt61w4AwIAmCCAAAAmCCAAgAkCCABgggACAJgggAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACACQIIAGCCYaRIKz+DO/0OFvUjXYNFH330Uc81u3fv9lxz/fXXe66R/A387O3t9VxzySWXeK7xczz4PYYuu+wyzzU9PT2ea/Ly8jzXDBvm7+Xbz7DUVOEMCABgggACAJjwHEBbt27VjTfeqJKSEgUCAW3YsCHhceecVqxYoeLiYmVnZ6u6ulp79+5NVr8AgCHCcwB1d3eroqJCq1ev7vfxVatW6emnn9Zzzz2n7du369JLL9Xs2bN9vS8KABi6PH+KVVNTo5qamn4fc87pqaee0sMPP6ybbrpJkvTiiy+qqKhIGzZs0K233nph3QIAhoykfgbU1tam9vZ2VVdXx+8LhUKqrKxUU1NTvzWxWEzRaDRhAQAMfUkNoPb2dklSUVFRwv1FRUXxx76urq5OoVAovpSWliazJQDAAGV+Fdzy5csViUTiy/79+61bAgCkQVIDKBwOS5I6OjoS7u/o6Ig/9nXBYFC5ubkJCwBg6EtqAJWVlSkcDqu+vj5+XzQa1fbt21VVVZXMTQEABjnPV8EdPXpULS0t8dttbW3atWuX8vPzNXbsWC1dulS/+c1vdOWVV6qsrEyPPPKISkpKNHfu3GT2DQAY5DwH0I4dO3TDDTfEby9btkyStGDBAq1du1YPPviguru7dc8996izs1M/+tGPtGnTJl8znwAAQ1fADaTJdDr1ll0oFFIkEuHzIKRdZ2en5xo/AyuvvPJKzzXjx4/3XOOnN0n68ssvPdccPnzYc01OTo7nmpMnT3qu8SsYDHqu8TOU9auvvvJc09fX57lGkv70pz95rrnmmms8rX++r+PmV8EBAC5OBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATnv8cQ7o45+RlUHcgEEhhNxfOz9DxdH1N6RyInq6v6d///revujvvvNNzzYQJEzzXfPe73/Vck52d7bnm448/9lwjST09PZ5r8vLy0rIdP/xOjvbDz7TuzMxMzzVdXV2eayTp73//u+car9OwzxdnQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwM2GGkgUAg5YMr/Q7h9DPY0M/X4meo4bBh3r+lA32Q6+OPP+655s9//rOvbZWXl3uuKSsr81zz+eefe65J59BYP8dROvtLl3T93PoZRupnOK0kNTQ0eK5ZsWKFr22dC2dAAAATBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATAzYYaR9fX2ehn5mZHjPUr9DOP0MDvTDz9eUTu+9957nmr/97W+ea55//nnPNT/84Q8910hSTk6O55rOzk7PNX4GVmZlZXmu8XuM+xlGmq6fQT8/f372t+RvwOqIESM818RisbRsR5JaWlo810Sj0ZSsP7Bf4QAAQxYBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATA3YYaUZGxoAdxulncOCnn37quebw4cOea1pbWz3XbN682XONJB04cMBzzciRIz3XzJkzx3ONnyGSfut6e3s91/jZD36Ou9zcXM81kr/hnV6GB5/mZ7ConwGmfl9L/NT5qfnqq6881/gdNOvneH3//fc9rd/d3X1e6w3MV3gAwJBHAAEATHgOoK1bt+rGG29USUmJAoGANmzYkPD4woULFQgEEhY/b6EAAIY2zwHU3d2tiooKrV69+qzrzJkzR4cOHYovL7/88gU1CQAYejxfhFBTU6OamppvXCcYDCocDvtuCgAw9KXkM6CGhgYVFhZq4sSJWrx4sY4cOXLWdWOxmKLRaMICABj6kh5Ac+bM0Ysvvqj6+nr97ne/U2Njo2pqas56WWddXZ1CoVB8KS0tTXZLAIABKOm/B3TrrbfG/3311VdrypQpGj9+vBoaGjRz5swz1l++fLmWLVsWvx2NRgkhALgIpPwy7PLychUUFKilpaXfx4PBoHJzcxMWAMDQl/IAOnDggI4cOaLi4uJUbwoAMIh4fgvu6NGjCWczbW1t2rVrl/Lz85Wfn6/HHntM8+fPVzgcVmtrqx588EFdccUVmj17dlIbBwAMbp4DaMeOHbrhhhvit09/frNgwQI9++yz2r17t1544QV1dnaqpKREs2bN0q9//WsFg8HkdQ0AGPQ8B9CMGTO+cWDjP/7xjwtqyK/f//73nms++eQTX9vyMziws7PTc82xY8c81/iRl5fnq27cuHGea3p6ejzXRCIRzzV+hmlKUnZ2tueayy67zHONn/78HHd+BphK/r5PWVlZnmv8DDBNJz/fJz/73M9+8Dtw18/36bPPPvO0/vHjx89rPWbBAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMJP1PcifLjh07NHLkyPNef8uWLZ63kZHhL3+HDx/uucbPtFs/2/Ezzdnv1O3e3l7PNX4m8QYCAc81fiZHS9KXX36Zlm35qfFzDPmdNu1n0nJXV5fnGj9/piWd+yEzM9NXnVfp+lmS5OuvTk+cONHT+t3d3ee1HmdAAAATBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATAzYYaR79uzxNFjzkksu8bwNP8M+JX9DF/0Md/QzhNMPv8NI/QzU9DN00U9/fvedn2Gufvg5Hk6ePOm55sSJE55rJH/95eXlea7xM+wznT9LfoeYpmM7I0aM8LUtPwNgt27d6mn9np6e81qPMyAAgAkCCABgggACAJgggAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACACQIIAGCCAAIAmCCAAAAmBuww0nnz5ik3N/e819+xY4fnbbS0tHiukaTjx497rvEzuNPPIEk/Q1n9DjX0MxzTz76LxWJpqZGkgwcPpm1bXvkZWOl3mGa6vqZhw7y/BPn5WRro/AxYraio8LWtTz75xHPNhAkTPK1/vgOEOQMCAJgggAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACACQIIAGCCAAIAmCCAAAAmCCAAgAkCCABgIuD8TMFLoWg0qlAopEgk4mkYaTodOHDAc42fIZf//e9/Pdd89NFHnmv8DCeUpEgk4rkmGAx6rsnLy/NcM3r0aM81kjRy5EjPNX7681MzatQozzV+hn1KUkaG9/+bZmdnp2U7gUDAc41fw4cP91zjpz8/NX6PcT8Di70639dxzoAAACYIIACACU8BVFdXp2uvvVY5OTkqLCzU3Llz1dzcnLBOT0+PamtrNWrUKI0cOVLz589XR0dHUpsGAAx+ngKosbFRtbW12rZtmzZv3qwTJ05o1qxZ6u7ujq9z//3364033tBrr72mxsZGHTx4UDfffHPSGwcADG6ePqHctGlTwu21a9eqsLBQO3fu1PTp0xWJRPSXv/xF69at009+8hNJ0po1a/Ttb39b27Zt0w9+8IPkdQ4AGNQu6DOg01dB5efnS5J27typEydOqLq6Or7OpEmTNHbsWDU1NfX7HLFYTNFoNGEBAAx9vgOor69PS5cu1XXXXafJkydLktrb25WVlXXGJaZFRUVqb2/v93nq6uoUCoXiS2lpqd+WAACDiO8Aqq2t1Z49e/TKK69cUAPLly9XJBKJL/v377+g5wMADA6+fkttyZIlevPNN7V161aNGTMmfn84HFZvb686OzsTzoI6OjoUDof7fa5gMOjrlxMBAIObpzMg55yWLFmi9evXa8uWLSorK0t4fOrUqRo+fLjq6+vj9zU3N2vfvn2qqqpKTscAgCHB0xlQbW2t1q1bp40bNyonJyf+uU4oFFJ2drZCoZDuvvtuLVu2TPn5+crNzdV9992nqqoqroADACTwFEDPPvusJGnGjBkJ969Zs0YLFy6UJP3hD39QRkaG5s+fr1gsptmzZ+uPf/xjUpoFAAwdDCMFACQVw0gBAAMaAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwQQAAAEwQQAMAEAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATHgKoLq6Ol177bXKyclRYWGh5s6dq+bm5oR1ZsyYoUAgkLDce++9SW0aADD4eQqgxsZG1dbWatu2bdq8ebNOnDihWbNmqbu7O2G9RYsW6dChQ/Fl1apVSW0aADD4DfOy8qZNmxJur127VoWFhdq5c6emT58ev3/EiBEKh8PJ6RAAMCRd0GdAkUhEkpSfn59w/0svvaSCggJNnjxZy5cv17Fjx876HLFYTNFoNGEBAAx9ns6A/r++vj4tXbpU1113nSZPnhy///bbb9e4ceNUUlKi3bt366GHHlJzc7Nef/31fp+nrq5Ojz32mN82AACDVMA55/wULl68WG+99ZbeffddjRkz5qzrbdmyRTNnzlRLS4vGjx9/xuOxWEyxWCx+OxqNqrS0VJFIRLm5uX5aAwAYikajCoVC53wd93UGtGTJEr355pvaunXrN4aPJFVWVkrSWQMoGAwqGAz6aQMAMIh5CiDnnO677z6tX79eDQ0NKisrO2fNrl27JEnFxcW+GgQADE2eAqi2tlbr1q3Txo0blZOTo/b2dklSKBRSdna2WltbtW7dOv30pz/VqFGjtHv3bt1///2aPn26pkyZkpIvAAAwOHn6DCgQCPR7/5o1a7Rw4ULt379fd955p/bs2aPu7m6VlpZq3rx5evjhh8/785zzfe8QADAwpeQzoHNlVWlpqRobG708JQDgIsUsOACACQIIAGCCAAIAmCCAAAAmCCAAgAkCCABgggACAJgggAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACACQIIAGCCAAIAmCCAAAAmCCAAgAkCCABgggACAJgggAAAJgggAIAJAggAYIIAAgCYIIAAACYIIACAiWHWDXydc06SFI1GjTsBAPhx+vX79Ov52Qy4AOrq6pIklZaWGncCALgQXV1dCoVCZ3084M4VUWnW19engwcPKicnR4FAIOGxaDSq0tJS7d+/X7m5uUYd2mM/nMJ+OIX9cAr74ZSBsB+cc+rq6lJJSYkyMs7+Sc+AOwPKyMjQmDFjvnGd3Nzci/oAO439cAr74RT2wynsh1Os98M3nfmcxkUIAAATBBAAwMSgCqBgMKiVK1cqGAxat2KK/XAK++EU9sMp7IdTBtN+GHAXIQAALg6D6gwIADB0EEAAABMEEADABAEEADAxaAJo9erV+ta3vqVLLrlElZWVev/9961bSrtHH31UgUAgYZk0aZJ1Wym3detW3XjjjSopKVEgENCGDRsSHnfOacWKFSouLlZ2draqq6u1d+9em2ZT6Fz7YeHChWccH3PmzLFpNkXq6up07bXXKicnR4WFhZo7d66am5sT1unp6VFtba1GjRqlkSNHav78+ero6DDqODXOZz/MmDHjjOPh3nvvNeq4f4MigF599VUtW7ZMK1eu1AcffKCKigrNnj1bhw8ftm4t7a666iodOnQovrz77rvWLaVcd3e3KioqtHr16n4fX7VqlZ5++mk999xz2r59uy699FLNnj1bPT09ae40tc61HyRpzpw5CcfHyy+/nMYOU6+xsVG1tbXatm2bNm/erBMnTmjWrFnq7u6Or3P//ffrjTfe0GuvvabGxkYdPHhQN998s2HXyXc++0GSFi1alHA8rFq1yqjjs3CDwLRp01xtbW389smTJ11JSYmrq6sz7Cr9Vq5c6SoqKqzbMCXJrV+/Pn67r6/PhcNh98QTT8Tv6+zsdMFg0L388ssGHabH1/eDc84tWLDA3XTTTSb9WDl8+LCT5BobG51zp773w4cPd6+99lp8nY8++shJck1NTVZtptzX94Nzzv34xz92P//5z+2aOg8D/gyot7dXO3fuVHV1dfy+jIwMVVdXq6mpybAzG3v37lVJSYnKy8t1xx13aN++fdYtmWpra1N7e3vC8REKhVRZWXlRHh8NDQ0qLCzUxIkTtXjxYh05csS6pZSKRCKSpPz8fEnSzp07deLEiYTjYdKkSRo7duyQPh6+vh9Oe+mll1RQUKDJkydr+fLlOnbsmEV7ZzXghpF+3RdffKGTJ0+qqKgo4f6ioiJ9/PHHRl3ZqKys1Nq1azVx4kQdOnRIjz32mK6//nrt2bNHOTk51u2ZaG9vl6R+j4/Tj10s5syZo5tvvlllZWVqbW3Vr371K9XU1KipqUmZmZnW7SVdX1+fli5dquuuu06TJ0+WdOp4yMrKUl5eXsK6Q/l46G8/SNLtt9+ucePGqaSkRLt379ZDDz2k5uZmvf7664bdJhrwAYT/qampif97ypQpqqys1Lhx4/TXv/5Vd999t2FnGAhuvfXW+L+vvvpqTZkyRePHj1dDQ4Nmzpxp2Flq1NbWas+ePRfF56Df5Gz74Z577on/++qrr1ZxcbFmzpyp1tZWjR8/Pt1t9mvAvwVXUFCgzMzMM65i6ejoUDgcNupqYMjLy9OECRPU0tJi3YqZ08cAx8eZysvLVVBQMCSPjyVLlujNN9/UO++8k/DnW8LhsHp7e9XZ2Zmw/lA9Hs62H/pTWVkpSQPqeBjwAZSVlaWpU6eqvr4+fl9fX5/q6+tVVVVl2Jm9o0ePqrW1VcXFxdatmCkrK1M4HE44PqLRqLZv337RHx8HDhzQkSNHhtTx4ZzTkiVLtH79em3ZskVlZWUJj0+dOlXDhw9POB6am5u1b9++IXU8nGs/9GfXrl2SNLCOB+urIM7HK6+84oLBoFu7dq3717/+5e655x6Xl5fn2tvbrVtLq1/84heuoaHBtbW1uX/+85+uurraFRQUuMOHD1u3llJdXV3uww8/dB9++KGT5J588kn34Ycfuk8//dQ559xvf/tbl5eX5zZu3Oh2797tbrrpJldWVuaOHz9u3HlyfdN+6Orqcg888IBrampybW1t7u2333bf+9733JVXXul6enqsW0+axYsXu1Ao5BoaGtyhQ4fiy7Fjx+Lr3HvvvW7s2LFuy5YtbseOHa6qqspVVVUZdp1859oPLS0t7vHHH3c7duxwbW1tbuPGja68vNxNnz7duPNEgyKAnHPumWeecWPHjnVZWVlu2rRpbtu2bdYtpd0tt9ziiouLXVZWlrv88svdLbfc4lpaWqzbSrl33nnHSTpjWbBggXPu1KXYjzzyiCsqKnLBYNDNnDnTNTc32zadAt+0H44dO+ZmzZrlRo8e7YYPH+7GjRvnFi1aNOT+k9bf1y/JrVmzJr7O8ePH3c9+9jN32WWXuREjRrh58+a5Q4cO2TWdAufaD/v27XPTp093+fn5LhgMuiuuuML98pe/dJFIxLbxr+HPMQAATAz4z4AAAEMTAQQAMEEAAQBMEEAAABMEEADABAEEADBBAAEATBBAAAATBBAAwAQBBAAwQQABAEwQQAAAE/8HzEPJ7BRPrG8AAAAASUVORK5CYII=\n"},"metadata":{}}]},{"cell_type":"markdown","source":["Преобразуем метки в one-hot encoding"],"metadata":{"id":"TW6hTPmBGpAR"}},{"cell_type":"code","source":["y_train = to_categorical(y_train, num_classes=len(labels_list))\n","y_test = to_categorical(y_test, num_classes=len(labels_list))"],"metadata":{"id":"B7XL4WUJ3vhJ","executionInfo":{"status":"ok","timestamp":1719734499748,"user_tz":-180,"elapsed":5,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":140,"outputs":[]},{"cell_type":"code","source":["# Дополнительное преобразование для выравнивания входных значений на слой Conv2D (на случай, если запутался).\n","x_train = np.expand_dims(x_train, axis=3)\n","x_test = np.expand_dims(x_test, axis=3)"],"metadata":{"id":"G-bel6iTlF4B","executionInfo":{"status":"ok","timestamp":1719734541960,"user_tz":-180,"elapsed":309,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":144,"outputs":[]},{"cell_type":"markdown","source":["### Создайте через Keras обычную нейронную сеть с именем model_simple без использования слоёв свёртки."],"metadata":{"id":"d9okwSzGKt_X"}},{"cell_type":"code","source":["model_simple = Sequential()\n","\n","model_simple.add(Flatten(input_shape=(28, 28)))\n","model_simple.add(Dense(128, activation='relu'))\n","model_simple.add(Dense(64, activation='relu'))\n","model_simple.add(Dense(len(labels_list), activation='softmax'))"],"metadata":{"id":"atNBwVlN3vYY","executionInfo":{"status":"ok","timestamp":1719734136763,"user_tz":-180,"elapsed":319,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":105,"outputs":[]},{"cell_type":"code","source":["model_simple.compile(optimizer='adam',\n","                     loss='categorical_crossentropy',\n","                     metrics=['accuracy'])"],"metadata":{"id":"uVfcWPjO3vPC","executionInfo":{"status":"ok","timestamp":1719734139419,"user_tz":-180,"elapsed":383,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":106,"outputs":[]},{"cell_type":"code","source":["model_simple.summary()"],"metadata":{"id":"JY1TQH3G4POz","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1719734141756,"user_tz":-180,"elapsed":315,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"0bcd54fa-e635-493e-fa0f-ce2b94da6789"},"execution_count":107,"outputs":[{"output_type":"stream","name":"stdout","text":["Model: \"sequential_4\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," flatten_3 (Flatten)         (None, 784)               0         \n","                                                                 \n"," dense_9 (Dense)             (None, 128)               100480    \n","                                                                 \n"," dense_10 (Dense)            (None, 64)                8256      \n","                                                                 \n"," dense_11 (Dense)            (None, 10)                650       \n","                                                                 \n","=================================================================\n","Total params: 109386 (427.29 KB)\n","Trainable params: 109386 (427.29 KB)\n","Non-trainable params: 0 (0.00 Byte)\n","_________________________________________________________________\n"]}]},{"cell_type":"markdown","source":["### Выберите настройки гиперпараметров, запустите обучение нейронной сети, подключив валидацию на тестовом множестве. Сохраните историю обучения в history_simple"],"metadata":{"id":"gRM9dogO2o6I"}},{"cell_type":"code","source":["history_simple = model_simple.fit(x_train, y_train,\n","                                  batch_size=128,\n","                                  epochs=14,\n","                                  verbose=1,\n","                                  validation_data=(x_test, y_test))"],"metadata":{"id":"NmMZIR6-4PLu","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1719734186151,"user_tz":-180,"elapsed":41546,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"41d4b583-2167-4d20-8fec-5e0a6bbf2d77"},"execution_count":108,"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/14\n","469/469 [==============================] - 5s 8ms/step - loss: 0.5554 - accuracy: 0.8096 - val_loss: 0.4689 - val_accuracy: 0.8310\n","Epoch 2/14\n","469/469 [==============================] - 4s 9ms/step - loss: 0.3926 - accuracy: 0.8598 - val_loss: 0.4055 - val_accuracy: 0.8559\n","Epoch 3/14\n","469/469 [==============================] - 2s 5ms/step - loss: 0.3530 - accuracy: 0.8721 - val_loss: 0.4374 - val_accuracy: 0.8344\n","Epoch 4/14\n","469/469 [==============================] - 2s 5ms/step - loss: 0.3267 - accuracy: 0.8823 - val_loss: 0.3655 - val_accuracy: 0.8687\n","Epoch 5/14\n","469/469 [==============================] - 2s 5ms/step - loss: 0.3080 - accuracy: 0.8867 - val_loss: 0.3530 - val_accuracy: 0.8730\n","Epoch 6/14\n","469/469 [==============================] - 3s 6ms/step - loss: 0.2965 - accuracy: 0.8898 - val_loss: 0.3454 - val_accuracy: 0.8720\n","Epoch 7/14\n","469/469 [==============================] - 4s 8ms/step - loss: 0.2799 - accuracy: 0.8965 - val_loss: 0.3312 - val_accuracy: 0.8800\n","Epoch 8/14\n","469/469 [==============================] - 2s 5ms/step - loss: 0.2682 - accuracy: 0.9010 - val_loss: 0.3362 - val_accuracy: 0.8811\n","Epoch 9/14\n","469/469 [==============================] - 3s 5ms/step - loss: 0.2619 - accuracy: 0.9025 - val_loss: 0.3312 - val_accuracy: 0.8792\n","Epoch 10/14\n","469/469 [==============================] - 2s 5ms/step - loss: 0.2513 - accuracy: 0.9064 - val_loss: 0.3210 - val_accuracy: 0.8839\n","Epoch 11/14\n","469/469 [==============================] - 3s 6ms/step - loss: 0.2423 - accuracy: 0.9104 - val_loss: 0.3239 - val_accuracy: 0.8854\n","Epoch 12/14\n","469/469 [==============================] - 3s 7ms/step - loss: 0.2335 - accuracy: 0.9123 - val_loss: 0.3554 - val_accuracy: 0.8714\n","Epoch 13/14\n","469/469 [==============================] - 3s 5ms/step - loss: 0.2285 - accuracy: 0.9147 - val_loss: 0.3505 - val_accuracy: 0.8705\n","Epoch 14/14\n","469/469 [==============================] - 2s 5ms/step - loss: 0.2204 - accuracy: 0.9175 - val_loss: 0.3190 - val_accuracy: 0.8889\n"]}]},{"cell_type":"code","source":["plt.plot(history_simple.history['accuracy'], 'g')\n","plt.plot(history_simple.history['val_accuracy'], 'r')\n","plt.legend(['accuracy', 'val_accuracy'])\n","plt.title(\"Точность\")\n","plt.show()"],"metadata":{"id":"hsK2hg17XQCV","colab":{"base_uri":"https://localhost:8080/","height":452},"executionInfo":{"status":"ok","timestamp":1719734400622,"user_tz":-180,"elapsed":490,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"7ddb06a0-9e48-45ca-9abe-7c8dc1ba1a3f"},"execution_count":115,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"iVBORw0KGgoAAAANSUhEUgAAAiwAAAGzCAYAAAAMr0ziAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABq9klEQVR4nO3dd1hT1x8G8DfsIQKyFERR3IIToW6tVlotddVW6rZqbd12iNtqlY6f1latVq2ruK12qHWUqq1bwS3uhSgIDqas5Pz+OCWIoBIM3ADv53nycLm5N/kmInk559xzVEIIASIiIiIDZqR0AUREREQvwsBCREREBo+BhYiIiAweAwsREREZPAYWIiIiMngMLERERGTwGFiIiIjI4DGwEBERkcFjYCEiIiKDx8BCREREBo+BhYgAACqVKl+3vXv3Kl0qEZVCJkoXQESG4eeff87x/apVq7B79+5c+2vXrl2UZRERAQBUXPyQiPIyfPhwLFiwAPwVQUSGgF1CRFQg9+7dw/vvvw8XFxdYWFigfv36WLlyZY5jVqxYAZVKhRs3buTY36ZNG7Rp00b7/d69e6FSqbBp06Zcz1OmTBn0798/x75r166hR48eKFeuHKysrPDKK69g27Ztuc5NTU3FtGnTUKNGDVhYWKBChQro1q0brl69ihs3bryw+yvrebNex/Hjxwv0XhHRy2OXEBHp7PHjx2jTpg2uXLmC4cOHo0qVKti4cSP69++PR48eYdSoUYX23DExMWjWrBlSUlIwcuRIODg4YOXKlXjrrbewadMmdO3aFQCgVqvx5ptvIjQ0FD179sSoUaOQmJiI3bt34+zZs2jfvn2O7q7Nmzdjy5YtOfZ5enoW2usgIt0wsBCRzhYvXoyIiAiEhISgV69eAIChQ4eidevWmDRpEgYOHAgbGxsYGclGXH12K3355ZeIiYnBv//+ixYtWgAABg8ejHr16mHs2LHo3LkzjIyMsGrVKoSGhmLOnDkYM2aM9vygoCAIIaBSqdC7d2/t/itXrmDLli059hGR4WCXEBHpbPv27ShfvjwCAwO1+0xNTTFy5EgkJSVh3759AABnZ2cAwO3bt/P1uImJiYiLi8txy+u5fX19tWEFkN1GQ4YMwY0bN3D+/HkAwC+//AJHR0eMGDEi12OoVKr8v9gnxMfHIy4uDomJiQU6n4gKjoGFiHR28+ZNVK9eXduCkiXrCqKbN28CABo2bAgLCwt8/vnnuHz5sjaEZGRk5Pm4AwcOhJOTU45bcnJyrueuWbNmrnOffu6rV6+iZs2aMDHRX0Ny+/bt4eTkhLJly8Le3h4fffRRrvqIqHCwS4iICo2LiwvmzZuHYcOGoUaNGjnua926da7jp0yZgpYtW+bYFxAQUKg16mLBggWoUaMG0tLSsHfvXvzvf/8DAPzwww8KV0ZU8jGwEJHOKleujNOnT0Oj0eRoZblw4YL2/iyDBg1Ct27dcPbsWaSnpwMAPv744zwf19vbG+3bt8+xz9jYONdzX7x4Mde5Tz+3p6cnjhw5goyMDJiamur6EvPk6+sLHx8fAECnTp1w6tQp7NixQy+PTUTPxy4hItJZx44dER0djfXr12v3ZWZmYt68eShTpkyu1pNy5cqhVatWaN++Pdq3bw97e/uXeu6jR4/i0KFD2n3JyclYvHgxPDw8UKdOHQBA9+7dERcXh/nz5+d6DH0NAtZoNLkCFREVDrawEJHOhgwZgh9//BH9+/dHWFgYPDw8sGnTJhw4cABz586FjY1NoT13UFAQ1q5dizfeeAMjR45EuXLlsHLlSly/fh2//PKLtsWnb9++WLVqFcaOHYujR4+iZcuWSE5Oxl9//YWPPvoInTt31vm5Dx06hLi4OG2XUGhoKD755BN9v0QiygMDCxHpzNLSEnv37kVQUBBWrlyJhIQE1KxZE8uXL881yZu+ubi44ODBgxg3bhzmzZuH1NRU1KtXD3/88Qc6deqkPc7Y2Bjbt2/HzJkzsWbNGvzyyy9wcHBAixYt4O3tXaDnHjlyJADAzMwMlSpVwpQpUzBx4kS9vC4iej5OzU9EREQGj2NYiIiIyOAxsBAREZHBY2AhIiIig8fAQkRERAaPgYWIiIgMHgMLERERGbwSMw+LRqPBnTt3YGNjU+CVWImIiKhoCSGQmJgIV1fXXAuqPqnEBJY7d+7A3d1d6TKIiIioACIjI1GxYsVn3l9iAkvWVOCRkZEoW7aswtUQERFRfiQkJMDd3f2FS3qUmMCS1Q1UtmxZBhYiIqJi5kXDOTjoloiIiAweAwsREREZvAIFlgULFsDDwwMWFhbw8/PD0aNHn3lsRkYGpk+fDk9PT1hYWKB+/frYsWNHjmOCg4PRpEkT2NjYwNnZGV26dMHFixcLUhoRERGVQDqPYVm/fj3Gjh2LRYsWwc/PD3PnzoW/vz8uXrwIZ2fnXMdPmjQJISEhWLJkCWrVqoWdO3eia9euOHjwIBo2bAgA2LdvH4YNG4YmTZogMzMTEyZMQIcOHXD+/HlYW1u//Kv8j1qtRkZGht4ej0oeY2NjmJiY8NJ4IiIDoxJCCF1O8PPzQ5MmTTB//nwAcv4Td3d3jBgxAkFBQbmOd3V1xcSJEzFs2DDtvu7du8PS0hIhISF5PkdsbCycnZ2xb98+tGrVKl91JSQkwNbWFvHx8XkOuk1KSsLt27eh48ulUsjKygoVKlSAmZmZ0qUQEZV4L/r8zqJTC0t6ejrCwsIwfvx47T4jIyO0b98ehw4dyvOctLQ0WFhY5NhnaWmJ/fv3P/N54uPjAQDlypV75jFpaWlIS0vTfp+QkPDMY9VqNW7fvg0rKys4OTnxr2fKkxAC6enpiI2NxfXr11G9evXnTmJERERFR6fAEhcXB7VaDRcXlxz7XVxccOHChTzP8ff3x5w5c9CqVSt4enoiNDQUmzdvhlqtzvN4jUaD0aNHo3nz5vDy8npmLcHBwfj888/zVXdGRgaEEHBycoKlpWW+zqHSydLSEqamprh58ybS09NzhW0iIlJGof/5+N1336F69eqoVasWzMzMMHz4cAwYMOCZf7kOGzYMZ8+exbp16577uOPHj0d8fLz2FhkZ+cJa2LJC+cFWFSIiw6PTb2ZHR0cYGxsjJiYmx/6YmBiUL18+z3OcnJzw66+/Ijk5GTdv3sSFCxdQpkwZVK1aNdexw4cPx9atW7Fnz57nTs8LAObm5tpJ4jhZHBERUcmmU2AxMzND48aNERoaqt2n0WgQGhqKpk2bPvdcCwsLuLm5ITMzE7/88gs6d+6svU8IgeHDh2PLli34+++/UaVKFR1fBhEREZVkOl/WPHbsWPTr1w8+Pj7w9fXF3LlzkZycjAEDBgAA+vbtCzc3NwQHBwMAjhw5gqioKDRo0ABRUVGYNm0aNBoNPvvsM+1jDhs2DGvWrMFvv/0GGxsbREdHAwBsbW055oSIiIh0DyzvvvsuYmNjMWXKFERHR6NBgwbYsWOHdiDurVu3cowBSE1NxaRJk3Dt2jWUKVMGHTt2xM8//ww7OzvtMQsXLgQAtGnTJsdzLV++HP3799f9VREREVGJovM8LIbqeddxp6am4vr166hSpQqv+nhJGRkZMDU1VbqMQsWfFyIiKVOTiRN3T2Dvjb04c+8MVnZZqfcLWPI7D0upvBxCCIHk9GRFbrrmwx07dqBFixaws7ODg4MD3nzzTVy9elV7/+3btxEYGIhy5crB2toaPj4+OHLkiPb+P/74A02aNIGFhQUcHR3RtWtX7X0qlQq//vprjuezs7PDihUrAAA3btyASqXC+vXr0bp1a1hYWGD16tW4f/8+AgMD4ebmBisrK3h7e2Pt2rU5Hkej0eDrr79GtWrVYG5ujkqVKmHmzJkAgFdffRXDhw/PcXxsbCzMzMxyjI8iIqKipdaocfzOcfzv4P/w5po34fC1A3yX+uKzvz7Dz6d/xo1HNxSrTecuoZIgJSMFZYLLKPLcSeOTYG2W/+UGkpOTMXbsWNSrVw9JSUmYMmUKunbtipMnTyIlJQWtW7eGm5sbfv/9d5QvXx7h4eHQaDQAgG3btqFr166YOHEiVq1ahfT0dGzfvl3nmoOCgjB79mw0bNgQFhYWSE1NRePGjTFu3DiULVsW27ZtQ58+feDp6QlfX18A8rLzJUuW4Ntvv0WLFi1w9+5d7Vw9gwYNwvDhwzF79myYm5sDAEJCQuDm5oZXX31V5/qIiKhg1Bo1TsWcwt4be7Hnxh78c/MfJKTlnIjVzsIOrSq3QluPtihjpsxnJ1BKA0tx0r179xzfL1u2DE5OTjh//jwOHjyI2NhYHDt2TDsrcLVq1bTHzpw5Ez179swxwV79+vV1rmH06NHo1q1bjn2ffPKJdnvEiBHYuXMnNmzYAF9fXyQmJuK7777D/Pnz0a9fPwCAp6cnWrRoAQDo1q0bhg8fjt9++w3vvPMOAGDFihXo378/58ohIipEGqHB6ZjT2HN9D/be3It/bv6DR6mPchxja26LVpVboY1HG7T1aIt6LvVgbGSsTMFPKJWBxcrUCknjkxR7bl1cvnwZU6ZMwZEjRxAXF6dtPbl16xZOnjyJhg0bPnMJg5MnT2Lw4MEvXbOPj0+O79VqNWbNmoUNGzYgKioK6enpSEtLg5WVfG0RERFIS0tDu3bt8nw8CwsL9OnTB8uWLcM777yD8PBwnD17Fr///vtL10pERNk0QoMzMWdytKA8TH2Y4xgbMxttC0objzZoUL6BQQSUp5XKwKJSqXTqllFSQEAAKleujCVLlsDV1RUajQZeXl5IT09/4SXfL7pfpVLlGlOT12rWT6+Y/c033+C7777D3Llz4e3tDWtra4wePRrp6en5el5Adgs1aNAAt2/fxvLly/Hqq6+icuXKLzyPiIieTSM0OHfvHPbc2IO9N/Zi3819ePD4QY5jbMxs0LJyS7Sp3AZtq7RFg/INYGJk+HHA8Cssxe7fv4+LFy9iyZIlaNmyJQDkWDSyXr16WLp0KR48eJBnK0u9evUQGhqqnSPnaU5OTrh79672+8uXLyMlJeWFdR04cACdO3dG7969AcgBtpcuXUKdOnUAANWrV4elpSVCQ0MxaNCgPB/D29sbPj4+WLJkCdasWaNd/ZuIiPJPIzQ4H3te24Ky78Y+3H98P8cx1qbWOQJKowqNikVAeVrxq7gUsbe3h4ODAxYvXowKFSrg1q1bCAoK0t4fGBiIWbNmoUuXLggODkaFChVw4sQJuLq6omnTppg6dSratWsHT09P9OzZE5mZmdi+fTvGjRsHQF6tM3/+fDRt2hRqtRrjxo3L1yXL1atXx6ZNm3Dw4EHY29tjzpw5iImJ0QYWCwsLjBs3Dp999hnMzMzQvHlzxMbG4ty5c3j//fe1j5M1+Nba2jrH1UtERJQ3IQQi4iK0Y1D23tiLuJS4HMdYmVqhRaUW2i6exhUaw9S4+E9HwcBiwIyMjLBu3TqMHDkSXl5eqFmzJr7//nvtBHtmZmbYtWsXPv74Y3Ts2BGZmZmoU6cOFixYAEBOxLdx40bMmDEDX375JcqWLYtWrVppH3/27NkYMGAAWrZsCVdXV3z33XcICwt7YV1ZEwH6+/vDysoKQ4YMQZcuXRAfH689ZvLkyTAxMcGUKVNw584dVKhQAUOHDs3xOIGBgRg9ejQCAwM53wkRUR6EELgQd0HbgrL3xl7EpsTmOMbK1ArN3ZtrB8n6uPqUiIDyNE4cR4q5ceMGPD09cezYMTRq1EjpcrT480JESklIS0DYnTAciTqCo1FHcTDyIGKScy44bGFigebuzbUtKE3cmsDM2Eyhil9efieOYwsLFbmMjAzcv38fkyZNwiuvvGJQYYWIqKhkqDNw9t5ZbTg5EnUEEbEREMjZjmBhYoFm7s3QpnIbtPFoA183X5ibmCtUtXIYWKjIHThwAG3btkWNGjWwadMmpcshIip0QgjceHQjRzgJvxuO1MzUXMdWtq0MXzdf+Lr5ws/ND03cmsDChK29DCxU5Nq0aaPzEgVERMXJg8cPcDTqaI7b02NPADlJ29PhpHyZ8gpUbPgYWIiIiF5CamYqTkWfytF6cuXBlVzHmRqZokH5Btpw4uvmi+oO1WGkKpXL+umMgYWIiCifNEKDy/cva8PJ0aijOBl9Ehma3JNuVi9XPUc4qV++Prt2XgIDCxER0TPEJMVoW02ORh3FsTvHcq29AwCOVo7aYJLVtVPOMu9lU6hgGFiIiKjUE0LgdsJtnIs9hzMxZ3DszjEciTqCW/G3ch1rYWKBxhUa52g98bDz4OKthYyBhYiISg0hBKKTonEu9hzO3juLc/fO4VysvCWkJeQ6XgUV6jjVyRFOvJy9SuTEbIaOgYWIiEqk2OTYXMHk7L2zuVYrzmJiZIIaDjVQ16kuGlVoBD83PzR2bYyy5s+ezIyKDgNLCebh4YHRo0dj9OjRSpdCRFRoHj5+mGcwyesyYgAwUhmhWrlqqOtUF3Wd6sLL2Qt1neuihkONYj1jbEnHwEJERMVCQloCzseezxVM7ibdfeY5Ve2r5gomtRxr8WqdYoiBhQySWq2GSqWCkRHnJyAqbZLTkxERF5ErmEQmRD7znEq2lXIFk9qOtWFtZl2ElVNhKp2fBkIAycnK3PI5w+vixYvh6uoKjUaTY3/nzp0xcOBAXL16FZ07d4aLiwvKlCmDJk2a4K+//irwWzJnzhx4e3vD2toa7u7u+Oijj5CUlJTjmAMHDqBNmzawsrKCvb09/P398fCh7AvWaDT4+uuvUa1aNZibm6NSpUqYOXMmAGDv3r1QqVR49OiR9rFOnjwJlUqFGzduAABWrFgBOzs7/P7776hTpw7Mzc1x69YtHDt2DK+99hocHR1ha2uL1q1bIzw8PEddjx49wgcffAAXFxdYWFjAy8sLW7duRXJyMsqWLZtr+v9ff/0V1tbWSExMLPD7RUT6c/3hdQT/G4y31r6Fqt9VhU2wDZosaYIBvw3A/w79D39e+VMbVlxtXPFa1dcw2m80lgYsxaH3DyE+KB43R9/E9l7b8U2Hb9CvQT/4uPowrJQwpbOFJSUFKFNGmedOSgKsX/yfqEePHhgxYgT27NmDdu3aAQAePHiAHTt2YPv27UhKSkLHjh0xc+ZMmJubY9WqVQgICMDFixdRqVIlncsyMjLC999/jypVquDatWv46KOP8Nlnn+GHH34AIANGu3btMHDgQHz33XcwMTHBnj17oFarAQDjx4/HkiVL8O2336JFixa4e/cuLly4oFMNKSkp+Oqrr7B06VI4ODjA2dkZ165dQ79+/TBv3jwIITB79mx07NgRly9fho2NDTQaDd544w0kJiYiJCQEnp6eOH/+PIyNjWFtbY2ePXti+fLlePvtt7XPk/W9jY2Nzu8TEenHg8cPsPHcRoScCcH+W/tz3e9s7ZyrxaSuU13YW9orUC0ZBFFCxMfHCwAiPj4+132PHz8W58+fF48fP5Y7kpKEkG0dRX9LSsr3a+rcubMYOHCg9vsff/xRuLq6CrVanefxdevWFfPmzdN+X7lyZfHtt9/m+/metHHjRuHg4KD9PjAwUDRv3jzPYxMSEoS5ublYsmRJnvfv2bNHABAPHz7U7jtx4oQAIK5fvy6EEGL58uUCgDh58uRz61Kr1cLGxkb88ccfQgghdu7cKYyMjMTFixfzPP7IkSPC2NhY3LlzRwghRExMjDAxMRF79+595nPk+nkhIr14nPFYbDq3SXRZ10WYTjcVmAaBaRCqaSrRbmU78d3h78Se63vEvaR7SpdKReh5n99PKp0tLFZWsqVDqefOp169emHw4MH44YcfYG5ujtWrV6Nnz54wMjJCUlISpk2bhm3btuHu3bvIzMzE48ePcetW7kmO8uOvv/5CcHAwLly4gISEBGRmZiI1NRUpKSmwsrLCyZMn0aNHjzzPjYiIQFpamrYlqKDMzMxQr169HPtiYmIwadIk7N27F/fu3YNarUZKSor2dZ48eRIVK1ZEjRo18nxMX19f1K1bFytXrkRQUBBCQkJQuXJltGrV6qVqJaL80QgN/r35L0JOh2Dj+Y2IT4vX3tegfAP09u6Nnl494VbWTcEqqTgonYFFpcpXt4zSAgICIITAtm3b0KRJE/z777/49ttvAQCffPIJdu/ejf/973+oVq0aLC0t8fbbbyM9PV3n57lx4wbefPNNfPjhh5g5cybKlSuH/fv34/3330d6ejqsrKxgaWn5zPOfdx8A7cBZ8cT4nYyM3OtuWFpa5popsl+/frh//z6+++47VK5cGebm5mjatKn2db7ouQFg0KBBWLBgAYKCgrB8+XIMGDCAM1ISFbJz984h5HQIVp9ZnWOwrHtZd/Ty7oVe9XrBy9lLwQqpuCmdgaWYsLCwQLdu3bB69WpcuXIFNWvWRKNGjQDIAbD9+/dH165dAQBJSUnaAay6CgsLg0ajwezZs7XhYsOGDTmOqVevHkJDQ/H555/nOr969eqwtLREaGgoBg0alOt+JycnAMDdu3dhby/7n0+ePJmv2g4cOIAffvgBHTt2BABERkYiLi4uR123b9/GpUuXntnK0rt3b3z22Wf4/vvvcf78efTr1y9fz01EurmTeAdrz6xFyJkQnIw+qd1va26LHnV6oHe93mhZuSVXJ6YCYWAxcL169cKbb76Jc+fOoXfv3tr91atXx+bNmxEQEACVSoXJkyfnuqIov6pVq4aMjAzMmzcPAQEBOHDgABYtWpTjmPHjx8Pb2xsfffQRhg4dCjMzM+zZswc9evSAo6Mjxo0bh88++wxmZmZo3rw5YmNjce7cObz//vuoVq0a3N3dMW3aNMycOROXLl3C7Nmz81Vb9erV8fPPP8PHxwcJCQn49NNPc7SqtG7dGq1atUL37t0xZ84cVKtWDRcuXIBKpcLrr78OALC3t0e3bt3w6aefokOHDqhYsWKB3iciyi0xLRGbIzYj5EwIQq+FQkC2pJoamaJTjU7o7d0bnWp04rwn9PKKZERNEdBp0G0xolarRYUKFQQAcfXqVe3+69evi7Zt2wpLS0vh7u4u5s+fL1q3bi1GjRqlPUaXQbdz5swRFSpUEJaWlsLf31+sWrUq10DZvXv3imbNmglzc3NhZ2cn/P39tfer1WrxxRdfiMqVKwtTU1NRqVIlMWvWLO25+/fvF97e3sLCwkK0bNlSbNy4MdegW1tb21x1hYeHCx8fH2FhYSGqV68uNm7cmOt13b9/XwwYMEA4ODgICwsL4eXlJbZu3ZrjcUJDQwUAsWHDhhe+F8X554WoKKRnpoutF7eKnpt6CssvLLWDZzENosWyFmLRsUXifsp9pcukYiK/g25VQuRzYhADl5CQAFtbW8THx6Ns2ZzrPqSmpuL69euoUqUKLCyY8kujn3/+GWPGjMGdO3dgZvb8qbf580KUmxACR6OOIuR0CNadW4e4lOyu2ZoONdGnXh+85/0eqthXUbBKKo6e9/n9JHYJUYmWkpKCu3fv4ssvv8QHH3zwwrBCRDldeXAFq0+vRsiZEFx5cEW738XaBYFegehdrzcaVWjEgexU6BhYSoHVq1fjgw8+yPO+ypUr49y5c0VcUdH5+uuvMXPmTLRq1Qrjx49XuhyiYiE2ORYbzm1AyJkQHL59WLvfytQK3Wp3Q2/v3mhXtR1MjPgRQkWHXUKlQGJiImJiYvK8z9TUFJUrVy7iigxbaf95odIpJSMFf1z8AyFnQrDjyg5kajIByJWNO3h2QG/v3uhcqzPKmCk0SziVWOwSIi0bGxtOQ09Euag1auy9sRchZ0Lwy/lfkJievb6Wj6sPenv3xrte76J8mfIKVkkklarAUkIak6iQ8eeESrKswbNrz67FhnMbcDfprvY+DzsP9PbujV71eqGWYy0FqyTKrVQEFmNjYwBAenp6vmZGpdItJSUFgOwuIyopzt47i7Vn1mLduXW49vCadr+9hT3erfsuetfrjWbuzTh4lgxWqQgsJiYmsLKyQmxsLExNTbWzuRI9SQiBlJQU3Lt3D3Z2dtqgS1RcXXt4TRtSzt47q91vbWqNzrU6I9ArEB08O8DMmFfPkeErFYFFpVKhQoUKuH79Om7evKl0OWTg7OzsUL48++ypeLqbeBfrz63H2rNrcTTqqHa/mbEZ3qj2BgK9AhFQMwBWpvlfiJXIEJSKwALIlYCrV69eoMUBqfQwNTVlywoVOw8eP8Av53/B2rNrsffGXu30+EYqI7Sr0g49vXqiW+1usLOwU7ZQopdQagILIFcN5mWqRFQSJKUn4feLv2Pt2bXYeWUnMjTZK6A3c2+GQK9A9KjTAy5lXBSskkh/SlVgISIqztIy07Djyg6sPbsWv1/8HY8zH2vvq+9SH4FegXjX61142HkoVyRRIWFgISIyYJmaTOy5vgdrz67F5ojNiE+L195XrVw1BHoFoqdXT9RxqqNglUSFj4GFiMjACCFw6PYhrD2zFhvOb8C95Hva+9xs3PBu3XcR6B2IxhUa8zJkKjUYWIiIDIAQAqdjTmPt2bVYd3YdbsZnX9HoYOmAt+u8jUCvQLSs3BJGKk7NQKUPAwsRkYKuPLiCtWfWYu3ZtYiIi9DuL2NWBl1qdUGgVyBeq/oaTI05kSGVbgwsRERFSAiB2wm3sfH8Rqw9uxbH7xzX3mdubI6O1Tsi0CsQnWp04lwpRE9gYCEi0rNMTSYi4yNx9eFVXHt4DVcfXMW1R/99fXgtx8BZY5Ux2lVth0CvQHSt1RW2FrYKVk5kuBhYiIgKICEtAdceXssOJA+vaQPKzfibyNRkPvf85u7N5VwpdXvA2dq5iKomKr4YWIiI8qARGtxJvJNnILn68CriUuKee765sTmq2FeBp70nqtpXzf5azhMedh7s7iHSEQMLEZVajzMe4/qj63kGkusPryNNnfbc8x2tHPMMJFXtq8LVxpVX8xDpEQMLEZV4mZpM7LyyE2F3w3IEkzuJd557nomRCSrbVs4zkFS1r4qy5mWL6BUQUYECy4IFC/DNN98gOjoa9evXx7x58+Dr65vnsRkZGQgODsbKlSsRFRWFmjVr4quvvsLrr79e4MckIsqPO4l3sDR8KZaEL8HthNt5HlPWvCw87T1lELHLDiSe9p5wt3WHiRH/riMyBDr/T1y/fj3Gjh2LRYsWwc/PD3PnzoW/vz8uXrwIZ+fcA8cmTZqEkJAQLFmyBLVq1cLOnTvRtWtXHDx4EA0bNizQYxIRPYtGaPD39b+x8PhC/HbhN6iFGoDsvnmzxpuoXq56jhaTcpblOFssUTGgEkIIXU7w8/NDkyZNMH/+fACARqOBu7s7RowYgaCgoFzHu7q6YuLEiRg2bJh2X/fu3WFpaYmQkJACPWZeEhISYGtri/j4eJQty2ZaotLmfsp9rDi5Aj+G/YjLDy5r97eo1AIf+nyI7rW7w9zEXMEKiSgv+f381qmFJT09HWFhYRg/frx2n5GREdq3b49Dhw7leU5aWhosLCxy7LO0tMT+/fsL/JhZj5uWlj0gLiEhQZeXQkQlgBACh28fxqKwRVh/dr12kKyNmQ361u+LoT5D4eXspXCVRKQPOgWWuLg4qNVquLi45Njv4uKCCxcu5HmOv78/5syZg1atWsHT0xOhoaHYvHkz1Gp1gR8TAIKDg/H555/rUj4RlRCJaYlYc2YNFh5fiFMxp7T7G5ZviA99PkSgdyDKmJVRsEIi0rdCH0323XffYfDgwahVqxZUKhU8PT0xYMAALFu27KUed/z48Rg7dqz2+4SEBLi7u79suURkwM7EnMHC4wsRcjoEiemJAAALEwv09OqJD30+RBPXJhyPQlRC6RRYHB0dYWxsjJiYmBz7Y2JiUL58+TzPcXJywq+//orU1FTcv38frq6uCAoKQtWqVQv8mABgbm4Oc3P2RxOVdKmZqdh0fhMWHl+Ig5EHtftrOtTEUJ+h6Fu/L8pZllOwQiIqCjrNamRmZobGjRsjNDRUu0+j0SA0NBRNmzZ97rkWFhZwc3NDZmYmfvnlF3Tu3PmlH5OISq4rD67g012fouKciuizpQ8ORh6EiZEJetTpgdC+oYgYFoHRr4xmWCEqJXTuEho7diz69esHHx8f+Pr6Yu7cuUhOTsaAAQMAAH379oWbmxuCg4MBAEeOHEFUVBQaNGiAqKgoTJs2DRqNBp999lm+H5OISodMTSb+uPgHFh5fiN3Xdmv3u5d1x5DGQ/B+w/dRwaaCghUSkVJ0DizvvvsuYmNjMWXKFERHR6NBgwbYsWOHdtDsrVu3YGSU3XCTmpqKSZMm4dq1ayhTpgw6duyIn3/+GXZ2dvl+TCIq2aISorAkfAmWhC/Rzj6rggqvV3sdH/p8iI7VO8LYyFjhKolISTrPw2KoOA8LUfGiERr8de0vLDq+CL9f/F07wZuTlRPeb/g+hjQegir2VRSukogKW6HMw0JE9LLiUuK0E7xdeXBFu79V5VYY2ngoutXuxgneiCgXBhYiKnRCCByMPIhFYYuw8dxG7QRvZc3Lom89OcFbXee6CldJRIaMgYWICk1SehJ+PvUzFh5fiDP3zmj3N6rQSE7w5hUIazNrBSskouKCgYWI9E4IgbVn1+KTXZ/gbtJdAHKCt0CvQHzo8yF8XH04wRsR6YSBhYj06uy9sxi+fTj23dwHAKhiVwWj/Eahb/2+sLe0V7g6IiquGFiISC/iU+Mxbe80zDs6D2qhhqWJJSa0nIBPmn0CCxOLFz8AEdFzMLAQ0UsRQiDkdAg+3f0pYpLlEhtda3XFt/7forJdZYWrI6KSgoGFiArsVPQpDP9zOPbf2g8AqF6uOua9MQ/+1fwVroyIShoGFiLS2aPUR5iyZwoWHFsAjdDAytQKk1tNxphXxnAOFSIqFAwsRJRvGqHBqlOrMO6vcbiXfA8A0KNOD8zuMBvutu4KV0dEJRkDCxHlS/jdcAzfPhyHbh8CANRyrIV5b8xD+6rtFa6MiEoDBhYieq4Hjx9g8t+TsShsETRCA2tTa0xtPRWjXhkFM2MzpcsjolKCgYWI8qQRGiw7sQzjQ8cjLiUOANDTqyf+99r/4FbWTeHqiKi0YWAholyO3zmOYduH4WjUUQBAHac6mP/GfLSt0lbhyoiotGJgISKt+yn3MSF0ApaEL4GAgI2ZDaa1mYYRviNgamyqdHlEVIoxsBAR1Bo1loYvxYS/J+DB4wcAgF7evfDNa9+ggk0FhasjImJgISr1jtw+gmHbhyHsbhgAwNvZG/M7zkeryq0UroyIKBsDC1EpFZsci/Gh4/HTiZ8AAGXNy2J6m+kY5jsMJkb81UBEhoW/lYhKGbVGjR/DfsTEvyfiUeojAEDf+n3xVfuvUL5MeWWLIyJ6BgYWolLkUOQhDNs+DCeiTwAA6rvUx4KOC9C8UnOFKyMiej4GFqJS4F7yPYz7axxWnFwBALA1t8UXr36BoT5D2f1DRMUCf1MRlWCZmkwsPLYQk/dMRnxaPABgYIOBCG4fDGdrZ4WrIyLKPwYWohLq35v/Yvifw3E65jQAoFGFRljQcQFeqfiKwpUREemOgYWoBElXp+NQ5CEsPbEUIadDAAD2FvaY1W4WBjcaDGMjY4UrJCIqGAYWomLuyoMr2HllJ3Ze3Yk9N/YgKT0JAKCCCoMaDcKsdrPgaOWocJVERC+HgYWomElMS8Tf1//GzqsypFx7eC3H/U5WTnjN8zWM8hsFXzdfhaokItIvBhYiA6cRGpy4e0IbUA5GHkSmJlN7v4mRCZq7N4e/pz/8q/mjQfkGMFIZKVgxEZU4o0cDdnZAUBBgYaFICQwsRAYoOikau67uws6rO7H76m7EpsTmuN/T3lMbUNp6tIWNuY1ClRJRiXfsGPD994AQwGuvAc2VmbeJgYXIAKRlpmH/rf3YeXUndl3dhVMxp3LcX8asDF6t8qoMKZ7+8CznqVClRFSqqNXAhx/KsNKnj2JhBWBgIVKEEAKX7l/SdvPsvbEXKRkpOY5pXKExOnh2gL+nP5q6N4WZsZlC1RJRqbV4MRAWBtjaAt98o2gpDCxERSQ+NR6h10O1V/TcjL+Z4/7yZcprA8prVV+Dk7WTQpUSEQG4dw+YMEFuf/EF4OKiaDkMLESFRK1RI+xumDagHL59GGqh1t5vZmyGFpVaaLt56rnUg0qlUrBiIqInjBsHPHoENGwou4UUxsBCpEdRCVHabp6/rv2FB48f5Li/hkMNbUBp49EG1mbWClVKRPQcBw4AK1bI7R9+AIyVn3SSgYXoJcWnxmP1mdVYGr5UuwpyFltzW7Sr2g7+nv7o4NkBHnYeyhRJRJRfmZnARx/J7fffB14xjOU8GFiICuj4neP48fiPWHN2jXbArAoqNHFrom1F8avox9WQiah4WbAAOH0aKFcO+PJLpavR4m9SIh0kpSdh7Zm1+DHsR4TdDdPur+NUBx80/gDveb/HafCJqPi6exeYPFluBwcDjobz+4yBhSgfTsecxqLjixByOgSJ6YkA5KDZHnV64IPGH6BFpRYcMEtExd8nnwCJiYCvLzBokNLV5MDAQvQMjzMeY8O5DVgUtgiHbx/W7q9erjo+aPwB+jXox9YUooIQAoiJAa5dA65elV+vXQNq15ZXpjD8K2PPHmDNGvn+//ADYGRYS3wwsBA9JSI2Aj+G/YiVp1biUeojAHK9nq61umKoz1C08WjDtXqIXiQ9HbhxI2couXo1ezslJe/zLCzkujVUtDIygGHD5PaHHwKNGytbTx4YWIggp8b/JeIX/Bj2I/65+Y92v4edB4Y0GoIBDQegfJnyClZIZIAePMgdSLK+RkbKlpRnUakAd3fA0xOoWhXQaIDly2WXRP36QNu2Rfc6CJg7F4iIAJyc5CRxBoiBhUq1y/cvY3HYYqw4tQJxKXEAAGOVMQJqBuCDxh+gg2cHtqZQ6ZWZCdy+nXcguXZNTir2PFZW2YHk6a+VKwPm5tnHCiH/yg8JAd59Fzh+HKhUqVBfHv3n9m3g88/l9tdfA/b2ytbzDAwsVOpkqDPw28XfsOj4IoReD9Xur1i2IgY3Goz3G74Pt7JuClZIVIQSE7PHkDwdSG7ckKHlecqXzzuUeHoCzs75H4+iUgE//gicOwecOAF07w78+6/sIqLCNWYMkJwsFzbs21fpap6JgYVKjRuPbmBJ2BL8dOInxCTHAJDzprxR/Q0MbTwUb1R/g3OmUOmQkQFs2QLMny9DwfOYmQFVquTdSlKlCmCtx9marayAzZsBHx/ZwvLhh8CyZRyEW5h27QI2bZIz2RrgQNsn8bczlWiZmkxsv7wdi44vwo4rOyAg+9TLlymP9xu+j0GNBnH2WSo9oqPl6rs//gjcuZO938Eh70Di6Qm4uhbttOweHsC6dYC/v5wavkmT7FlXSb/S0oDhw+X2iBFAvXrK1vMCDCxUIt1OuI2l4UuxNHwpohKjtPtfq/oaPmj8Ad6q+RZMjU0VrJCoiAgBHD4sW1M2bpStK4BcefeDD4DBg4GKFZWt8Wnt28sZVj/7DBg1Sn6QtmihdFUlzzffAJcvy269rDEsBoyBhUoMtUaNXVd3YVHYImy9tBUaoQEAOFo5YmCDgRjceDCqlaumcJVEReTxY9lSMX8+EB6evb9ZM/lXdffusrvHUH3yiewW2rAB6NEDCAuTrT2kHzduADNnyu3Zs4GyZRUtJz8YWKjYi06KxrITy7A4bDFuxt/U7m9duTWG+gxF11pdYW5i/pxHICpBbtwAFi4Eli6Vlx0DcuDqe+/JeTYaNVK0vHxTqeT4lfPngbNngbfflhObmfP/sl6MGgWkpsrLxwMDla4mXxhYqNhSa9T4ZNcnmH9sPjI18koGewt79KvfD0MaD0Ftp9oKV0hURIQA/vpLtqb88Uf2/CceHnL8x8CBcpxKcWNtLQcHN2kCHDokP2QXLVK6quJv61bg998BExP5M1NMBjUzsFCxlJqZil6be2FzxGYAQDP3Zvig8QfoUacHLE0tFa6OqIgkJACrVskPnYsXs/e/9prs9unUqWgHzBaGatXkdPGdOsnBwj4+BrfGTbHy+DEwcqTcHjsWqFNH2Xp0wMBCxU5CWgK6rOuCPTf2wMzYDGu6rUH3Ot2VLouo6EREAAsWACtXAklJcp+NDdC/v2xRqVVL0fL07o03gBkzgEmTZLeWtzfg56d0VcVTcDBw/bocaJ21KnMxwcBCxUpMUgzeWP0GTkSfgI2ZDX7r+RvaVuEU3vQciYnA3bvyZmUl/6LU59whRSUzUzblz58PhGZPeIjatWVrSp8+MrSUVOPHy0G4v/4qBwyHhckrnSj/Ll8GvvpKbs+dC5Qpo2g5uirQDDELFiyAh4cHLCws4Ofnh6NHjz73+Llz56JmzZqwtLSEu7s7xowZg9TUVO39arUakydPRpUqVWBpaQlPT0/MmDED4nnrUFCpc/3hdbRY3gInok/AycoJe/vvZVgprYSQ08JHRAB//y2nc//mG9nE3bMn0Lo1UKOG/AAvWxaoWRNo0wbw9ZX7PD2Bt94CJkyQ3Q2nT8s5KQxRXJy8xNfTE+jaVYYVIyOgSxc5buXcOdmqUpLDCiBf88qVsvUoKkpeOZR1iTa9mBByrpX0dDnHTbduSlekO6GjdevWCTMzM7Fs2TJx7tw5MXjwYGFnZydiYmLyPH716tXC3NxcrF69Wly/fl3s3LlTVKhQQYwZM0Z7zMyZM4WDg4PYunWruH79uti4caMoU6aM+O677/JdV3x8vAAg4uPjdX1JVAycij4lyv+vvMA0CI+5HuJS3CWlS6LCoNEIcf++EGfOCLFrlxArVwoRHCzEyJFC9OghRPPmQlStKoSlpRDyV3D+bjY2QlSvLoSz87OPMTYWolYtId5+W4ipU4XYuFGIiAghMjKUeS+OHROiXz8hzM2za3RwECIoSIgbN5SpyRBcuCD/PQEhRoxQupri45df5HtmZibEJcP6/Znfz2+VELo1Y/j5+aFJkyaYP38+AECj0cDd3R0jRoxAUFBQruOHDx+OiIgIhD7RhPnxxx/jyJEj2L9/PwDgzTffhIuLC3766SftMd27d4elpSVCQkLyVVdCQgJsbW0RHx+PssXgenLKv39v/ouAtQGIT4uHt7M3dvTeAVcbzsdQrGg0wP37cnbVrO6ZvLajo3Vr6bCzAypUkDdX1+ztp79/suk7Nla2Spw9K29Z289ayM/MTP5V7+Ulb3Xryq8eHvqfxjwtTU6TPm8ecORI9v7GjeVfx+++y7V1AHmFS+fOcnvlSoNe/8YgJCfLrsPISDkOaMYMpSvKIb+f3zqNYUlPT0dYWBjGjx+v3WdkZIT27dvj0KFDeZ7TrFkzhISE4OjRo/D19cW1a9ewfft29OnTJ8cxixcvxqVLl1CjRg2cOnUK+/fvx5w5c55ZS1paGtKe+MWWkJCgy0uhYuKPi3/gnU3vIDUzFS0qtcAfgX/AzsJO6bIoP9LSgClTgLVrZRh50SJ6T3JwyF8QsSzAFWFOTrJ7qE2b7H1CyND0ZIA5e1bOAZKcLLuMTp/O+ThZ42GygkxWmHFz0/0y0du35RUwixcD9+7JfaamMqAMHy67sorJpadF4q235M/W9Olytl4vr+Izv4wSZsyQYcXDQ44FKqZ0CixxcXFQq9VweWqgk4uLCy5cuJDnOe+99x7i4uLQokULCCGQmZmJoUOHYsKECdpjgoKCkJCQgFq1asHY2BhqtRozZ85Er169nllLcHAwPi8GUwlTwa08uRLv//4+1EKNN2u8ifVvr4eVqZXSZVF+RETIyahOncq539n5xUGkfPminxxMpZJBw81N9u9n0WiAmzdzB5mICCAlRQ4CPX4852PZ2uZsicm6OTnlPE4I4J9/5CDaLVsAtVrud3MDhg6VU+ZzUOmzTZ0qB95u2ybH9oSFAY6OSldleCIi5Ey2APD99zJoF1e69DNFRUUJAOLgwYM59n/66afC19c3z3P27NkjXFxcxJIlS8Tp06fF5s2bhbu7u5g+fbr2mLVr14qKFSuKtWvXitOnT4tVq1aJcuXKiRUrVjyzltTUVBEfH6+9RUZGcgxLCfLNgW8EpkFgGkS/Lf1Eema60iVRfmg0QixalD3GxNFRiPXrhYiMFCK9BP0bZmTIsRSbNgkxbZocX1O7thwH86wxMk5OQrRtK8ddzJwphJdXzvtbt5bjZkrS+1TYHj4Uolo1+f69+qpy440MlUYjf+YAIQIClK7mmfI7hkWnwJKWliaMjY3Fli1bcuzv27eveOutt/I8p0WLFuKTTz7Jse/nn38WlpaWQq1WCyGEqFixopg/f36OY2bMmCFq1qyZ79o46LZk0Gg04tNdn2rDyic7PxEajUbpsig/4uKE6No1+wP4tdeEuHNH6aqKVmqqEKdOCbFmjRATJgjx1ltCeHoKoVLlHWKsrIT44AMhTp9WuvLi6+xZIayt5fv51GdNqbdmjXxfLCyEuHZN6WqeKb+f3zp1CZmZmaFx48YIDQ1Fly5dAMhBt6GhoRietUT1U1JSUmD01MA04/9mXhT/jfd91jEajUaX8qiYy9RkYvAfg7Hi5AoAwNftv8anzT9VtijKnz175DwgUVFy7EVwMDBmjP4HpRo6c3O5snC9ejn3JyfLpvmsrqXr1+UihAMGAPb2ytRaUtStC6xYIS9z/t//5ADlnj2Vrkp5CQnAxx/L7QkTgCpVlK1HH3RNQuvWrRPm5uZixYoV4vz582LIkCHCzs5OREdHCyGE6NOnjwgKCtIeP3XqVGFjYyPWrl0rrl27Jnbt2iU8PT3FO++8oz2mX79+ws3NTXtZ8+bNm4Wjo6P47LPP8l0XW1iKt5T0FBGwJkBgGoTx58ZiWfgypUui/EhPF2L8+OwWhJo1hQgLU7oqKo3GjctutTp1SulqlDdmjHw/qlUT4vFjpat5rkLpEsoyb948UalSJWFmZiZ8fX3F4cOHtfe1bt1a9OvXT/t9RkaGmDZtmvD09BQWFhbC3d1dfPTRR+Lhw4faYxISEsSoUaNEpUqVhIWFhahataqYOHGiSEtLy3dNDCzF18PHD0WLZS0EpkFYfGEhfrvwm9IlUX5cvixEkybZ3RuDBwuRlKR0VVRaZWYK0aGD/FmsWlXO51NanT6dPZ5qxw6lq3mhQpuHxVBxHpbi6W7iXby++nWcjjkNW3Nb/B74O1pVbqV0WfQ8QsgF94YPl+vY2NsDS5bI6dKJlHT/vlwc8cYN4PXX5VIGxX3xR10JAbRqBezfL/9PbtqkdEUvlN/P71LWwUyG5MqDK2i+rDlOx5xG+TLlsa//PoYVQ/foEfDee3KRvaQkOQX+qVMMK2QYHBzkJeKWlsCOHXKultJm1SoZVqytgW+/VboavWJgIUWcuHsCzZc1x/VH1+Fp74kDAw+gfvn6SpdFz3PwINCgAbBunfyr9Ysv5Lo27u5KV0aUrUEDYOlSuT1rFrB5s6LlFKmHD4FP/7tQYcqUEvd/k4GFitzeG3vRekVr3Eu+hwblG+DAwAOoal9V6bLoWTIz5YyiLVvKSdSqVJF/wU2cWPqa26l4eO89eZUaAPTrJ2csLg0mT5ZLT9SuDYwerXQ1esfAQkVqS8QW+If4IzE9Ea0rt8befnvhUoazeRqsmzeBtm3lrKIajbx0+eRJ4JVXlK6M6Pm+/louv5CUJGfCjY9XuqLCFR4OLFwotxcskGtglTAMLFRkloYvxdsb30a6Oh1danXBjt47YGthq3RZ9CwbNgD168vWFBsbICRE9o9zUDsVByYmwPr1slvk0iUZtkvq3F4aDfDRR/JrYKD8I6MEYmChQieEQPC/wRj8x2BohAaDGg7Cxh4bYWHCVWcNUlISMHCgXHgvPl62ppw8CTxnbS8ig+TsLMewmJsDf/whx12VRD/9JFf3trHJXjeoBGJgoUKlERqM3TkWE/6Wi12ObzEeiwMWw8RIp0mWqagcPy5XvV2+XM5SO3myXKCvKscYUTHl4wMsWiS3p06VlzqXJHFxQFCQ3J4+XS4gWkIxsFChyVBnoO+Wvph7ZC4AYE6HOZjVbhZUKpWyhVFuGo3s82/aFLh8GahYUU63P326nGqfqDjr3x8YNkxu9+olu4hKivHjgQcPAG9vOTdSCcbAQoUiOT0Zndd1xuozq2FiZIKfu/6MMU3HKF0W5SUqCnjtNWDcOHlF0NtvA6dPy8mniEqKOXOA5s3lGjtduwKJiUpX9PIOH86+hPuHH+S4nRKMgYX07sHjB3jt59fw55U/YWliid96/obe9XorXRbl5bff5MDav/8GrKzkL78NG7ggH5U8ZmZy1ldXV3mZ84ABclbY4kqtzm416tcPaNFC2XqKAAML6dXthNtoubwlDt0+BHsLe4T2DUXH6h2VLouelpIiryro0kVOZ96okbws8v33AXbZUUlVvrwMLaamwC+/AF99pXRFBbdokfw/a2cnu3NLAQYW0puLcRfRfFlznI89D1cbV/w74F80dW+qdFn0tNOngSZNsuds+PRT4NAhoGZNZesiKgpNmwLz58vtCROAnTuVracgYmLkxI0AMHOmvBqqFGBgIb04FnUMLZa3wK34W6jhUAMHBx5EXee6SpdFTxIC+P57wNdXNomXLw/s2iX/OiuBk0wRPdOQIcCgQfL/RGAgcO2a0hXp5rPP5JQDjRsDH3ygdDVFhoGFXtruq7vRdmVbxKXEwcfVB/sH7Edlu8pKl1X0NBrDnZjq3j3gzTeBUaOAtDS5ffq0HGxLVBrNnw/4+cn1d7p2BZKTla4of/79V07gqFLJgbalaHmMkj2kmArdhnMb0Htzb2RoMtCuSjtseXcLbMxtlC6raIWHy4mb1qyRVx44OQEuLi++OTkVzS+bHTvkZZ0xMXICrdmz5fgVjlWh0szcXI5nadxYhvfBg4HVqw37/0VGhvy/C8h6fX2VraeIMbBQgf1w7AcM3z4cAgI96vTAz11/hrmJudJlFY0HD+Qvt2XL5CywT4qOlrcXUakAR8f8hRtnZ93nQ0lLk3M0ZC0x7+UFrF0rvxKRnG9o40agXTv5f8PHBxg7Vumqnm3+fODsWcDBQa5EXcqohCjO13VlS0hIgK2tLeLj41GWa50UKiEEpu+bjmn7pgEAhjYeivkd58PYqIQ3TWo08vLfn34CtmyRgQCQ4z+6dZNX2NSuLVsyXnSLi9P9kspy5fIXblxcZJ98YCBw6pQ8d8QIeUWEpaV+3xOikmDePGDkSNniuWsX8OqrSleU2507QK1ashV3yRI5BqeEyO/nNwML6Wxi6ETM2i/T/dTWUzG19dSSPXvtrVvAihVyuvobN7L3168vQ0qvXjJM6CIzU4aW/ISb2Fg554IuVCoZiBwdZd1vvqnb+USliRCy23TVKvl/JiwMqFRJ6apyCgwE1q2Ta3sdOCCXzighGFioUHx3+DuM3jkaAPD9699jhN8IZQsqLGlpclK1n34Cdu/Obg2xtQXee08GlUaNiqa/W6ORc6XkJ9zcuyf7uQE5oHblyhK9tgiR3jx+LCdfCw+X41r+/ddwWiRDQ4H27WVIOX4caNhQ6Yr0Kr+f3xzDQvm25swabViZ+erMkhlWzpyRISUkRIaELG3bypDSrVvR/xIzMpIDdJ2cXjz+RAh51UNKCuDmZtgDCIkMiaWlXNm5cWPZwlKmjBwr4uQkW12y/g8+uf3k946OciCvvqWnZ68R9NFHJS6s6IKBhfJl55Wd6PdrPwDASN+RGN9ivMIV6VF8vGxq/ekn4Nix7P1ubrKZeMAAwNNTsfJ0olLJ7ildu6iICKhcWQ7C7dFD/sESGytv+WVjk3eYeVbQsbF58R8Vc+YAFy7IgfczZrzc6yvmGFjohY5GHUX3Dd2RqclEoFcgvn392+I/ZkUI2eT700/yF9Tjx3K/iQnw1luyNcXfv1TNcUBEkK2pd+/KoBIXlx1anrUdGyvDjVotB8QmJuZ/Ijozs+e32tjYZIeUb76R0/CXYgws9FwX4i6g4+qOSM5IRgfPDljRZQWMVMV4sNedO3Jcx7JlwJUr2ftr15YhpU+fUjPNNRE9g6mpXCTR1TV/x2s0wKNHeYeZZwWdx49ld09UlLw9T8uW8ndTKcfAQs90O+E2/EP8cf/xfTRxbYJf3vkFZsbFcAr3jAxg2zbZmvLnn9lX3JQpA/TsKYOKnx/HexBRwRgZZXfF5ndNrpSU/AUbQF7GzN9PDCyUtwePH+D1kNe1awNte28bypiVUbos3Vy4IFtSVq2SV9Bkad5chpQePWRoISIqalZWcsxM5VK4jEkBMbBQLikZKQhYG4BzsefgauOKXb13wcnaSemy8icpSY5J+eknOVdBFmdnoF8/YOBAOfkSEREVKwwslEOGOgPvbnoXByMPws7CDjt77zT8hQyFAA4fliFl/XoZWgA5YLZjR9ma0rGj7lPbExGRwWBgIS0hBIZsHYKtl7bCwsQCfwT+AS9nA193JjRUTjsfEZG9r1o1GVL69s3/oDkiIjJoDCykNT50PFacXAFjlTE2vL0BLSq1ULqk58vMlINm4+LkpE89esig0rIlB6gREZUwDCwEAPj20Lf46sBXAIDFAYsRUDNA4Yry4Z9/ZFhxcACuXpXT5hMRUYlUjCfUIH0JOR2CsbvkkurB7YIxsOFAhSvKp19+kV87d2ZYISIq4RhYSrk/L/+JAb8NAACM9huNcc3HKVxRPmk0wJYtcrt7d2VrISKiQsfAUooduX0Eb298G5maTPTy7oXZ/rOLz5T7hw7J6bNtbYF27ZSuhoiIChkDSykVERuBjms6IiUjBf6e/ljWeVnxmnI/qzsoIKBwVkglIiKDUow+oUhfIuMj4R/ijwePH8DXzReb3tlUvKbcF0IuAw+wO4iIqJRgYCllHjx+gNdXv47IhEjUdKhZPKfcDwsDbt4ErK3lispERFTiMbCUIikZKXhzzZs4H3sebjZu2NVnFxytHJUuS3dZ3UEdO8r5V4iIqMRjYCklMtQZ6LGxBw7dPgR7C3vs7L0TlWwrKV2W7oTIDizsDiIiKjUYWEoBjdBg0B+DsP3ydliaWGLre1tR17mu0mUVzNmzwOXLcqBtx45KV0NEREWEgaUUCPorCKtOrZJT7vfYgGbuzZQuqeCyWlf8/QEbG2VrISKiIsPAUsLNPjgb3xz8BgCw9K2leLPGmwpX9JLYHUREVCoxsJRgq06twie7PwEAfNX+K/Rv0F/Zgl7WxYuyS8jERM6/QkREpQYDSwm1/fJ2DPxNrgk09pWx+LTZpwpXpAdZrSvt2gH29srWQkRERYqBpQQ6FHkIb294G2qhRu96vfFNh2+Kz5T7z8PuICKiUouBpYQ5H3sendZ0wuPMx3ij2htY9lYxm3L/Wa5fB8LDASMjoEsXpashIqIiVgI+yShL1pT7D1Mf4pWKr2Bjj40wNTZVuiz9yJqKv1UrwMlJ2VqIiKjIMbCUEPdT7qNDSAfcTriN2o61sTVwK6zNrJUuS3/YHUREVKoxsJQAyenJ6LSmEy7EXUDFshWxs/dOOFg5KF2W/kRFAYcOye1u3ZSthYiIFMHAUsxlTbl/JOqIdsp9d1t3pcvSry1b5NdmzQBXV2VrISIiRTCwFGMaocHA3wfizyt/wtLEEtve24Y6TnWULkv/2B1ERFTqMbAUU0IIfLrrU4ScDoGxyhgbe2xEU/emSpelf7GxwD//yG12BxERlVoMLMXU/w7+D3MOzwEALOu8DJ1qdFK4okLy66+ARgM0bgx4eChdDRERKaRAgWXBggXw8PCAhYUF/Pz8cPTo0eceP3fuXNSsWROWlpZwd3fHmDFjkJqamuOYqKgo9O7dGw4ODrC0tIS3tzeOHz9ekPJKvJUnV+Kzvz4DAHzz2jfoW7+vwhUVInYHERERABNdT1i/fj3Gjh2LRYsWwc/PD3PnzoW/vz8uXrwIZ2fnXMevWbMGQUFBWLZsGZo1a4ZLly6hf//+UKlUmDNHthA8fPgQzZs3R9u2bfHnn3/CyckJly9fhj2nX89l66WteP/39wEAnzT9BJ80+0ThigrRw4dAaKjcZmAhIirVVEIIocsJfn5+aNKkCebPnw8A0Gg0cHd3x4gRIxAUFJTr+OHDhyMiIgKhWR88AD7++GMcOXIE+/fvBwAEBQXhwIED+Pfffwv8QhISEmBra4v4+HiULVu2wI9jyA5GHkT7Ve3xOPMx+tbvi+Wdl5eMWWyfZdUqoF8/wMsLOHNG6WqIiKgQ5PfzW6dPu/T0dISFhaF9+/bZD2BkhPbt2+NQ1jwZT2nWrBnCwsK03UbXrl3D9u3b0bFjR+0xv//+O3x8fNCjRw84OzujYcOGWLJkyXNrSUtLQ0JCQo5bSXY/5T7eXPMmHmc+RqfqnbA0YGnJDisAu4OIiEhLp0+8uLg4qNVquLi45Njv4uKC6OjoPM957733MH36dLRo0QKmpqbw9PREmzZtMGHCBO0x165dw8KFC1G9enXs3LkTH374IUaOHImVK1c+s5bg4GDY2tpqb+7uJWzukafsvrYbD1Mfonq56tjQY0PJmXL/WRITgZ075TYDCxFRqVfof6Lv3bsXs2bNwg8//IDw8HBs3rwZ27Ztw4wZM7THaDQaNGrUCLNmzULDhg0xZMgQDB48GIsWLXrm444fPx7x8fHaW2RkZGG/FEUdipQtWK9Xex1WplYKV1MEtm0D0tKA6tVllxAREZVqOg26dXR0hLGxMWJiYnLsj4mJQfny5fM8Z/LkyejTpw8GDRoEAPD29kZycjKGDBmCiRMnwsjICBUqVECdOjknPKtduzZ+yeoSyIO5uTnMzc11Kb9YO3RbBpamFUvgXCt5ebI7SKVSthYiIlKcTi0sZmZmaNy4cY4BtBqNBqGhoWjaNO8P0pSUFBgZ5XwaY2NjAHLyMwBo3rw5Ll68mOOYS5cuoXLlyrqUV2I9zniME9EnAKBkTg73tJQUYPt2uc3uICIiQgEuax47diz69esHHx8f+Pr6Yu7cuUhOTsaAAQMAAH379oWbmxuCg4MBAAEBAZgzZw4aNmwIPz8/XLlyBZMnT0ZAQIA2uIwZMwbNmjXDrFmz8M477+Do0aNYvHgxFi9erMeXWnyF3w1HpiYTLtYuqGxbCkLczp0ytFSuLCeMIyKiUk/nwPLuu+8iNjYWU6ZMQXR0NBo0aIAdO3ZoB+LeunUrR4vKpEmToFKpMGnSJERFRcHJyQkBAQGYOXOm9pgmTZpgy5YtGD9+PKZPn44qVapg7ty56NWrlx5eYvGn7Q5ybwpVaegeyeoO6taN3UFERASgAPOwGKqSPA9L9w3dsTliM75q/xU+a/6Z0uUUrrQ0wNkZSEgADhyQKzQTEVGJVSjzsFDRE0JorxAqFQNuQ0NlWHF1BV55RelqiIjIQDCwGLjIhEjcTboLEyMTNHYtBeM5srqDunYFjPjjSUREEj8RDFxW60p9l/olf/6VzEzgt9/kNq8OIiKiJzCwGLhSNf/Kvn3A/fuAoyPQsqXS1RARkQFhYDFwWYGluXNj4MMPgZ9+UriiQpTVHdSlC2Ci8wVsRERUgvFTwYClZqbixF05YVy7f24DixbJD/K2bYGqVRWuTs80GmDLFrnN7iAiInoKW1gMWPjdcGRoMuBi6QTHH3+WOzMzgenTlS2sMBw8CERHA7a2wKuvKl0NEREZGAYWA5Y14HZEbFWoLl0CLC3lHT//DEREKFhZIcjqDnrrLcDMTNlaiIjI4DCwGLCs8Su9Q2PljhEjgM6dZffJtGnKFaZvQuRc7JCIiOgpDCwG7PDtw2h4B6h84pocuzJiBDBjhpyufsMG4ORJpUvUj2PHgMhIwNoa6NBB6WqIiMgAMbAYqMj4SEQlRuHjw/+tpfPuu0DFioC3t9wGgClTlCtQn7JaVzp1yu72IiIiegIDi4E6dPsQ3OKBd8/+t9TT2LHZd37+uZwF9o8/gMOHlSlQX9gdRERE+cDAYqAORR7CiKOAiQZAmzZAo0bZd9aoAfTrJ7cnTVKiPP05fRq4ehWwsAA6dlS6GiIiMlAMLAbq9NUD+OD4f9882bqSZcoUwNRULha4Z0+R1qZXWa0r/v5AmTLK1kJERAaLgcUApWWmof72cNilAemeVeTYjqd5eABDhsjtSZNk10pxxO4gIiLKBwYWAxR++xiGH1QDAEw//vTZqxZPmCC7Ug4eBHbsKMIK9eTCBeD8edlSFBCgdDVERGTAGFgMUNyapaj6CEgoYwZV1liVvLi6AsOHy+3i2MqS1brSvj1gZ6doKUREZNgYWAxQ9VVbAQBnujcHrKyef/C4cXLsR3h49lo8xQW7g4iIKJ8YWAzN4cOodfE+0owB1bDhLz7e0REYM0ZuT54MqNWFW5++XLsGnDgBGBvL2XuJiIieg4HFwKR8NRMAsKaeCvXr++fvpLFjZZfK+fPAunWFV5w+bd4sv7ZuLUMXERHRczCwGJLr12H5+zYAwJ9v1oS1mXX+zrOzAz77TG5PnQpkZBROffrE7iAiItIBA4sh+f57qDQCOz0BJ79XdTt3xAjA2VlOwrZyZeHUpy+3b8sZelUqoGtXpashIqJigIHFUDx6BCxdCgCY0xR4peIrup1fpgwwfrzcnj4dSEvTb336lDU4uFkzoEIFZWshIqJigYHFUCxdCiQl4ZyzCrs8gabuTXV/jKFDATc3ufLx4sX6r1FfNm2SX9kdRERE+cTAYggyMoDvvwcAzH5FwNHaEZ72nro/joWFvFIIAGbOBJKT9ViknsTEAP/+K7e7dVO2FiIiKjYYWAzBpk1AZCSS7ctgjTfQtGJTqFSqgj3WgAFAlSoyGCxYoN869eHXX+UEdz4+QOXKSldDRETFBAOL0oQA5swBAGztUBlppgUYv/IkMzNg2jS5/dVXQHz8y9eoT7w6iIiICoCBRWn//gscPw5YWCC47kMAsoXlpfTqBdSqBTx4AMyd+/I16suDB9krSzOwEBGRDhhYlPZf60py4Ns4pbkDI5URmrg1ebnHNDaWVwoBwOzZwP37L1mknvz+O5CZCXh7A9WrK10NEREVIwwsSrp8WX6IA9jfzQcAUM+lHsqYlXn5x+7eHahfH0hMBL755uUfTx/YHURERAXEwKKkuXPlGJZOnbDbLBIA8IrbS4xfeZKREfDFF3L7+++B6Gj9PG5BJSQAu3bJ7bffVrYWIiIqdhhYlPLgAbB8udz++GMcun0IQAHnX3mWTp0APz/g8WMgOFh/j1sQ27YB6elAzZpAnTrK1kJERMUOA4tSFi2SQaJBA6S3bIawO2EA9DDg9kkqlZyPJev5bt3S32Pr6snuoIJesk1ERKUWA4sS0tKAefPk9scf40T0SaSp0+Bo5Yhq5arp97natQPatpWtG1ldREUtJQX480+5zfErRERUAAwsSli3To4pcXUF3nkHh28fBiDnXynwhHHPkxVUli0DrlzR/+O/yI4dMrR4eAANGxb98xMRUbHHwFLUnpgoDiNHAmZm2vErehtw+7RmzYCOHQG1OntSuaLE7iAiInpJDCxFLTQUOH0asLYGhgwBgMIZcPu0GTPk1zVrgHPnCu95npaWBmzdKrfZHURERAXEwFLUslpXBg4E7O1xJ/EObsXfgpHKCL5uvoX3vI0aycAgBDBlSuE9z9P++kte0uzqKq9YIiIiKgAGlqJ0/rwcfKpSAaNGAYB2/Iq3s7d+Jox7ns8/l8+9eTMQFla4z5UlqzuoWzc5NwwREVEB8BOkKH37rfzapQvg6QkAOBT53/iVl1nwML/q1pXrDAHA5MmF/3wZGXJ1ZoDdQURE9FIYWIrKvXvAzz/L7Y8/1u7Wjl/R5/wrzzN1qlxr6M8/gQMHCve59u4FHj4EnJyAli0L97mIiKhEY2ApKj/8IAeg+vrKq3YApKvTcfzOcQCFPOD2SdWqyfEzADBpkhzTUliyuoO6dJEhiYiIqIAYWIrC48cysACydeW/S3tP/jdhXDnLcqherghXL540CTAzky0gf/9dOM+hVgNbtshtdgcREdFLYmApCiEhQGwsULmyHHz6n0KfMO5ZKlUChg6V2xMnFk4ry4EDshvMzk7OtEtERPQSGFgKm0aTPdh21CjAxER7V5GPX3nS+PGApSVw5IhcmFDfsrqD3npLtuYQERG9BAaWwrZjBxARAdjYAO+/n+OurCuEFAks5cvLmXYB2UWk0ejvsTUaeek0ALz9tv4el4iISi0GlsKWNVHc4MFA2bLa3XcT7+Jm/E2ooCrcCeOe59NPZU2nTmW3iOjDsWPA7dtAmTLAa6/p73GJiKjUYmApTKdOyan4jY2zWzP+kzV+xcvZCzbmNkpUBzg4AGPHyu0pU+RAWX3ICj9vvglYWOjnMYmIqFRjYClMWa0rb78tB9w+QdHxK08aMwYoVw64cAFYvfrlH0+InIsdEhER6QEDS2G5cwdYu1ZuZ7ViPKFIFjzMj7JlgXHj5Pa0aUB6+ss93qlTwLVrckDvG2+8dHlEREQAA0vhmT9fTk3fooWcLO4JOSaMU7qFBQCGDQNcXIDr14Hly1/usbJaV15/Xa5ITUREpAcFCiwLFiyAh4cHLCws4Ofnh6NHjz73+Llz56JmzZqwtLSEu7s7xowZg9TU1DyP/fLLL6FSqTB69OiClGYYkpOBRYvk9hPT8Gc5HXMaqZmpsLewR3WHIpww7lmsreV8LAAwYwbwjH+bfGF3EBERFQKdA8v69esxduxYTJ06FeHh4ahfvz78/f1x7969PI9fs2YNgoKCMHXqVEREROCnn37C+vXrMWHChFzHHjt2DD/++CPq1aun+ysxJCtWyDV0PD2BgIBcdz+54KGRykAauYYMAdzdgaio7LClq4gIeTM1lQNuiYiI9ETnT8s5c+Zg8ODBGDBgAOrUqYNFixbBysoKy5Yty/P4gwcPonnz5njvvffg4eGBDh06IDAwMFerTFJSEnr16oUlS5bA3t6+YK/GEKjVwNy5cnvMmDzX0DGYAbdPMjeXVwoBwKxZQFKS7o+R1bry2muAra3+aiMiolJPp8CSnp6OsLAwtG/fPvsBjIzQvn17HDp0KM9zmjVrhrCwMG1AuXbtGrZv346OHTvmOG7YsGHo1KlTjsd+nrS0NCQkJOS4GYStW4ErVwB7e6B//zwPMZgBt0/r108ujhgbC8ybp/v5mzbJr+wOIiIiPdMpsMTFxUGtVsPFxSXHfhcXF0RHR+d5znvvvYfp06ejRYsWMDU1haenJ9q0aZOjS2jdunUIDw9HcHBwvmsJDg6Gra2t9ubu7q7LSyk8s2fLrx98kOeg0+ikaNx4dEPZCeOexdRUXikEAF9/DTx6lP9zr16VVwgZGwOdOxdGdUREVIoV+gCKvXv3YtasWfjhhx8QHh6OzZs3Y9u2bZgxYwYAIDIyEqNGjcLq1athocMkY+PHj0d8fLz2FhkZWVgvIf+OHQP+/Vd+8I8YkechWRPG1XWui7LmZfM8RlE9ewJ168qwkhW+8iOrO6hNGzkhHRERkR6ZvPiQbI6OjjA2NkZMTEyO/TExMShfvnye50yePBl9+vTBoEGDAADe3t5ITk7GkCFDMHHiRISFheHevXto1KiR9hy1Wo1//vkH8+fPR1paGozzGAdibm4Oc3NzXcovfFkTxfXsCbi65nmIousH5YexMTB9uuzWmTtXztDr5PTi83h1EBERFSKdWljMzMzQuHFjhIaGavdpNBqEhoaiadO8P4BTUlJgZJTzabICiBAC7dq1w5kzZ3Dy5EntzcfHB7169cLJkyfzDCsG6dYtYONGuZ3HRHFZDHLA7dO6dgUaNZIDb7/66sXHR0YCR48CKpU8l4iISM90amEBgLFjx6Jfv37w8fGBr68v5s6di+TkZAwYMAAA0LdvX7i5uWnHowQEBGDOnDlo2LAh/Pz8cOXKFUyePBkBAQEwNjaGjY0NvLy8cjyHtbU1HBwccu03aN9/L68QevVVoEGDPA/JUGdkTxhnaANun6RSAV98AXTsCCxYIAPYM1qMAGSvzNy8uVwFmoiISM90DizvvvsuYmNjMWXKFERHR6NBgwbYsWOHdiDurVu3crSoTJo0CSqVCpMmTUJUVBScnJwQEBCAmTNn6u9VKC0hAViyRG7nMVFcltMxp/E48zHsLOxQw6FGERVXQK+/LgPIgQPAzJkyuDxLVnfQ228XTW1ERFTqqIQQQuki9CEhIQG2traIj49H2bJFPJj1229lK0StWsC5c4BR3j1t84/Ox4g/R+D1aq/jz15/Fm2NBbF3L9C2rRxEfOkS4OGR+5joaNn6IoTsFjOUq7WIiKhYyO/nt4FMs1qMZWYC330nt8eMeWZYAYrJ+JUntWkDtG8v10SaPj3vY379VYYVX1+GFSIiKjQMLC9ryxbg5k3A0RHo0+e5hxr8FUJ5+eIL+XXlStnK8jReHUREREWAgeVlCJE9V8lHHwGWls88NCYpBtcfXTfMCeOex89Proek0QBTp+a87/59YM8euc3AQkREhYiB5WUcOgQcOSLX4fnoo+cemjVhXB2nOrC1KGbr7GR1B61bB5w+nb3/99/llVH168uFHomIiAoJA8vLyGpd6d0beGq5gqcVu/ErT2rQAHjnHbmdtUAiwO4gIiIqMgwsBXX1qhy/AsjBti9gsAse5tfnn8sBxb/9JpcgSEgAdu+W9zGwEBFRIWNgKajvvpNjWF5/Xa698xyZmkwcizoGAHil4itFUZ3+1aqVPah40iS5KnV6utxfp46ytRERUYmn88RxBODhQ2DZMrn9nInisjw5YVwtx1qFXFwhmjIFWL0a2LULuH5d7mPrChERFQG2sBTEkiVAcjLg7Q20a/fCw7MuZ/Zz84ORqhi/5VWrAv8tYonLl+VXBhYiIioCxfjTUyHp6XLdIEDObqtSvfCUYj3g9mkTJ8qrogCgSpVnrptERESkTwwsutq4EYiKkov8BQbm65SsS5qL7fiVJ1WsCIwcKbf79MlXYCMiInpZHMOiiycnihs+PLul4TnuJd/D1YdXAQB+Ff0Ks7qiExwMdOoENGumdCVERFRKMLDoYt8+4MQJOaPt0KH5OuXJCePsLOwKsbgiZGwMtG6tdBVERFSKsEtIF1mtK/37Aw4O+TqlWK4fREREZGAYWPLr4kU594hKBYwene/TDkeVoPErRERECmFgya+5c+XXgACgRo18nZKpycTRqKMA2MJCRET0MhhY8iMuDlixQm6PHZvv087EnEFKRgpszW1R26l24dRGRERUCjCw5MeiRUBqKtC4MdCqVb5Py5p/xa9iMZ8wjoiISGH8FH2R1FRg/ny5nc+J4rJkBZZX3Dh+hYiI6GUwsLzI2rVATIycMK1HD51Ozbqkudiu0ExERGQgGFieRwhgzhy5PXIkYGqa71Njk2Nx5cEVAHINISIiIio4BpbnefAAcHICypQBBg/W6dSs1pXajrVhb2lfGNURERGVGpzp9nkcHIC//wbu3gXs7HQ6tUQteEhERKQwtrDkR4UKOp9SohY8JCIiUhgDSyHIMWEcB9wSERG9NAaWQnD23lkkZySjrHlZ1HGqo3Q5RERExR4DSyHIWvDQz40TxhEREekDP00LARc8JCIi0i8GlkKQ1cLCK4SIiIj0g4FFz+JS4nD5wWUAbGEhIiLSFwYWPcu6nLmWYy1OGEdERKQnDCx6xvlXiIiI9I+BRc84wy0REZH+MbDokVqjzp4wjoGFiIhIbxhY9OjsvbNISk+CjZkNJ4wjIiLSIwYWPcrqDvJ184WxkbHC1RAREZUcDCx6lDXglt1BRERE+sXAokfaAbdc8JCIiEivGFj05H7KfVy6fwmAXEOIiIiI9IeBRU+yuoNqONSAg5WDwtUQERGVLAwsesLxK0RERIWHgUVPOGEcERFR4WFg0QO1Ro0jUUcAcMAtERFRYWBg0YNzseeQlJ6EMmZlUNeprtLlEBERlTgMLHqQNX6FE8YREREVDgYWPeD4FSIiosLFwKIHhyIZWIiIiAoTA8tLevD4AS7evwgAeKXiKwpXQ0REVDIxsLykI7fl1UHVy1XnhHFERESFhIHlJXH9ICIiosLHwPKSOOCWiIio8BUosCxYsAAeHh6wsLCAn58fjh49+tzj586di5o1a8LS0hLu7u4YM2YMUlNTtfcHBwejSZMmsLGxgbOzM7p06YKLFy8WpLQipdaotV1CDCxERESFR+fAsn79eowdOxZTp05FeHg46tevD39/f9y7dy/P49esWYOgoCBMnToVERER+Omnn7B+/XpMmDBBe8y+ffswbNgwHD58GLt370ZGRgY6dOiA5OTkgr+yIhARF4HE9ERYm1qjrjMnjCMiIiosJrqeMGfOHAwePBgDBgwAACxatAjbtm3DsmXLEBQUlOv4gwcPonnz5njvvfcAAB4eHggMDMSRI0e0x+zYsSPHOStWrICzszPCwsLQqlUrXUssMlmXM/u6+cLESOe3koiIiPJJpxaW9PR0hIWFoX379tkPYGSE9u3b49ChQ3me06xZM4SFhWm7ja5du4bt27ejY8eOz3ye+Ph4AEC5cuWeeUxaWhoSEhJy3Ioax68QEREVDZ2aBeLi4qBWq+Hi4pJjv4uLCy5cuJDnOe+99x7i4uLQokULCCGQmZmJoUOH5ugSepJGo8Ho0aPRvHlzeHl5PbOW4OBgfP7557qUr3e8QoiIiKhoFPpVQnv37sWsWbPwww8/IDw8HJs3b8a2bdswY8aMPI8fNmwYzp49i3Xr1j33ccePH4/4+HjtLTIysjDKf6YHjx/gQpwMaX5ufkX63ERERKWNTi0sjo6OMDY2RkxMTI79MTExKF++fJ7nTJ48GX369MGgQYMAAN7e3khOTsaQIUMwceJEGBllZ6bhw4dj69at+Oeff1CxYsXn1mJubg5zc3Ndytero1Gyi6tauWpwsnZSrA4iIqLSQKcWFjMzMzRu3BihoaHafRqNBqGhoWjaNO9ukZSUlByhBACMjeWKxkII7dfhw4djy5Yt+Pvvv1GlShWdXoQSuH4QERFR0dH50paxY8eiX79+8PHxga+vL+bOnYvk5GTtVUN9+/aFm5sbgoODAQABAQGYM2cOGjZsCD8/P1y5cgWTJ09GQECANrgMGzYMa9aswW+//QYbGxtER0cDAGxtbWFpaamv16pXHHBLRERUdHQOLO+++y5iY2MxZcoUREdHo0GDBtixY4d2IO6tW7dytKhMmjQJKpUKkyZNQlRUFJycnBAQEICZM2dqj1m4cCEAoE2bNjmea/ny5ejfv38BXlbh0ggNjkTJy7K54CEREVHhU4msfpliLiEhAba2toiPj0fZsmUL9bnO3TsHr4VesDa1xqOgR5yDhYiIqIDy+/nNtYQKIKs7qIlbE4YVIiKiIsDAUgAccEtERFS0GFgKIKuFheNXiIiIigYDi44epT5CRFwEAAYWIiKiosLAoqMjt+XVQZ72nnC2dla4GiIiotKBgUVHXD+IiIio6DGw6Eg7fsWN3UFERERFhYFFBxqh0XYJsYWFiIio6DCw6OBC3AXEp8XDytQK9VzqKV0OERFRqcHAooOs+VeauHLCOCIioqLEwKIDLnhIRESkDAYWHXDCOCIiImUwsOTTo9RHOB97HgAH3BIRERU1BpZ8Ohp1FABQ1b4qJ4wjIiIqYgws+cQFD4mIiJTDwJJPHL9CRESkHAaWfNAIDY5E/TdhHFtYiIiIihwDSz5cjLuIR6mPYGliyQnjiIiIFMDAkg9Z3UFN3JrA1NhU4WqIiIhKHwaWfMgacMsFD4mIiJTBwJIPh6MOA+D8K0REREphYHmB+NR4nLt3DgAH3BIRESmFgeUFjkYdhYBAFbsqcCnjonQ5REREpRIDywtw/hUiIiLlMbC8wOHb/41fYXcQERGRYhhYnkMjNNmBhQNuiYiIFGOidAGGLFOTieB2wTgadRT1XeorXQ4REVGppRJCCKWL0IeEhATY2toiPj4eZcuWVbocIiIiyof8fn6zS4iIiIgMHgMLERERGTwGFiIiIjJ4DCxERERk8BhYiIiIyOAxsBAREZHBY2AhIiIig8fAQkRERAaPgYWIiIgMHgMLERERGTwGFiIiIjJ4DCxERERk8BhYiIiIyOCZKF2AvmQtOp2QkKBwJURERJRfWZ/bWZ/jz1JiAktiYiIAwN3dXeFKiIiISFeJiYmwtbV95v0q8aJIU0xoNBrcuXMHNjY2UKlUenvchIQEuLu7IzIyEmXLltXb4xZ3fF9y43uSG9+TvPF9yY3vSW6l5T0RQiAxMRGurq4wMnr2SJUS08JiZGSEihUrFtrjly1btkT/wBQU35fc+J7kxvckb3xfcuN7kltpeE+e17KShYNuiYiIyOAxsBAREZHBY2B5AXNzc0ydOhXm5uZKl2JQ+L7kxvckN74neeP7khvfk9z4nuRUYgbdEhERUcnFFhYiIiIyeAwsREREZPAYWIiIiMjgMbAQERGRwWNgISIiIoPHwPICCxYsgIeHBywsLODn54ejR48qXZJigoOD0aRJE9jY2MDZ2RldunTBxYsXlS7LoHz55ZdQqVQYPXq00qUoLioqCr1794aDgwMsLS3h7e2N48ePK12WYtRqNSZPnowqVarA0tISnp6emDFjxgsXfCtp/vnnHwQEBMDV1RUqlQq//vprjvuFEJgyZQoqVKgAS0tLtG/fHpcvX1am2CLyvPckIyMD48aNg7e3N6ytreHq6oq+ffvizp07yhWsEAaW51i/fj3Gjh2LqVOnIjw8HPXr14e/vz/u3bundGmK2LdvH4YNG4bDhw9j9+7dyMjIQIcOHZCcnKx0aQbh2LFj+PHHH1GvXj2lS1Hcw4cP0bx5c5iamuLPP//E+fPnMXv2bNjb2ytdmmK++uorLFy4EPPnz0dERAS++uorfP3115g3b57SpRWp5ORk1K9fHwsWLMjz/q+//hrff/89Fi1ahCNHjsDa2hr+/v5ITU0t4kqLzvPek5SUFISHh2Py5MkIDw/H5s2bcfHiRbz11lsKVKowQc/k6+srhg0bpv1erVYLV1dXERwcrGBVhuPevXsCgNi3b5/SpSguMTFRVK9eXezevVu0bt1ajBo1SumSFDVu3DjRokULpcswKJ06dRIDBw7Msa9bt26iV69eClWkPABiy5Yt2u81Go0oX768+Oabb7T7Hj16JMzNzcXatWsVqLDoPf2e5OXo0aMCgLh582bRFGUg2MLyDOnp6QgLC0P79u21+4yMjNC+fXscOnRIwcoMR3x8PACgXLlyCleivGHDhqFTp045fl5Ks99//x0+Pj7o0aMHnJ2d0bBhQyxZskTpshTVrFkzhIaG4tKlSwCAU6dOYf/+/XjjjTcUrsxwXL9+HdHR0Tn+H9na2sLPz4+/d58QHx8PlUoFOzs7pUspUiVmtWZ9i4uLg1qthouLS479Li4uuHDhgkJVGQ6NRoPRo0ejefPm8PLyUrocRa1btw7h4eE4duyY0qUYjGvXrmHhwoUYO3YsJkyYgGPHjmHkyJEwMzNDv379lC5PEUFBQUhISECtWrVgbGwMtVqNmTNnolevXkqXZjCio6MBIM/fu1n3lXapqakYN24cAgMDS/wKzk9jYKECGTZsGM6ePYv9+/crXYqiIiMjMWrUKOzevRsWFhZKl2MwNBoNfHx8MGvWLABAw4YNcfbsWSxatKjUBpYNGzZg9erVWLNmDerWrYuTJ09i9OjRcHV1LbXvCekmIyMD77zzDoQQWLhwodLlFDl2CT2Do6MjjI2NERMTk2N/TEwMypcvr1BVhmH48OHYunUr9uzZg4oVKypdjqLCwsJw7949NGrUCCYmJjAxMcG+ffvw/fffw8TEBGq1WukSFVGhQgXUqVMnx77atWvj1q1bClWkvE8//RRBQUHo2bMnvL290adPH4wZMwbBwcFKl2Ywsn638vdubllh5ebNm9i9e3epa10BGFieyczMDI0bN0ZoaKh2n0ajQWhoKJo2bapgZcoRQmD48OHYsmUL/v77b1SpUkXpkhTXrl07nDlzBidPntTefHx80KtXL5w8eRLGxsZKl6iI5s2b57rk/dKlS6hcubJCFSkvJSUFRkY5f+UaGxtDo9EoVJHhqVKlCsqXL5/j925CQgKOHDlSan/vAtlh5fLly/jrr7/g4OCgdEmKYJfQc4wdOxb9+vWDj48PfH19MXfuXCQnJ2PAgAFKl6aIYcOGYc2aNfjtt99gY2Oj7VO2tbWFpaWlwtUpw8bGJtcYHmtrazg4OJTqsT1jxoxBs2bNMGvWLLzzzjs4evQoFi9ejMWLFytdmmICAgIwc+ZMVKpUCXXr1sWJEycwZ84cDBw4UOnSilRSUhKuXLmi/f769es4efIkypUrh0qVKmH06NH44osvUL16dVSpUgWTJ0+Gq6srunTpolzRhex570mFChXw9ttvIzw8HFu3boVardb+7i1XrhzMzMyUKrvoKX2ZkqGbN2+eqFSpkjAzMxO+vr7i8OHDSpekGAB53pYvX650aQaFlzVLf/zxh/Dy8hLm5uaiVq1aYvHixUqXpKiEhAQxatQoUalSJWFhYSGqVq0qJk6cKNLS0pQurUjt2bMnz98j/fr1E0LIS5snT54sXFxchLm5uWjXrp24ePGiskUXsue9J9evX3/m7949e/YoXXqRUglRyqZZJCIiomKHY1iIiIjI4DGwEBERkcFjYCEiIiKDx8BCREREBo+BhYiIiAweAwsREREZPAYWIiIiMngMLERERGTwGFiIiIjI4DGwEBERkcFjYCEiIiKD93+C9DaWvd6PpAAAAABJRU5ErkJggg==\n"},"metadata":{}}]},{"cell_type":"code","source":["plt.plot(history_simple.history['loss'], 'm')\n","plt.plot(history_simple.history['val_loss'], 'b')\n","plt.legend(['loss', 'val_loss'])\n","plt.title(\"Потери\")\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":452},"id":"xzroYoGQF--E","executionInfo":{"status":"ok","timestamp":1719734196594,"user_tz":-180,"elapsed":449,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"c5390182-3c86-45af-888c-66f4cd9ca86c"},"execution_count":110,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["### Создайте свёрточную нейронную сеть с именем model_cnn. Архитектуру необходимо подобрать, исходя из высокой точности на тестовом множестве."],"metadata":{"id":"ySk9acmXu2Pt"}},{"cell_type":"code","source":["model_cnn = Sequential()\n","# Слой 1\n","model_cnn.add(Conv2D(filters=6, kernel_size=(5, 5), padding='same', activation='tanh', input_shape=(28,28,1)))\n","model_cnn.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))\n","# Слой 2\n","model_cnn.add(Conv2D(filters=16,kernel_size=(5, 5), activation='tanh'))\n","model_cnn.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))\n","# Полносвязные слои\n","model_cnn.add(Flatten())\n","model_cnn.add(Dense(120, activation='tanh'))\n","model_cnn.add(Dense(84, activation='tanh'))\n","\n","# Выход\n","model_cnn.add(Dense(10, activation='softmax'))"],"metadata":{"id":"mttf6xempJJN","executionInfo":{"status":"ok","timestamp":1719734613372,"user_tz":-180,"elapsed":340,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":146,"outputs":[]},{"cell_type":"code","source":["model_cnn.compile(optimizer='adam',\n","                  loss='categorical_crossentropy',\n","                  metrics=['accuracy'])"],"metadata":{"id":"fKyo6A0hrsi6","executionInfo":{"status":"ok","timestamp":1719734616778,"user_tz":-180,"elapsed":300,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}}},"execution_count":147,"outputs":[]},{"cell_type":"code","source":["history_cnn = model_cnn.fit(x_train, y_train,\n","                            batch_size=60,\n","                            epochs=10,\n","                            verbose=1,\n","                            validation_data=(x_test, y_test))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"zU23GmTnrx8R","executionInfo":{"status":"ok","timestamp":1719735074621,"user_tz":-180,"elapsed":443988,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"036b52be-1565-4099-e5d7-3fc5484e4df2"},"execution_count":148,"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/10\n","1000/1000 [==============================] - 40s 39ms/step - loss: 0.4800 - accuracy: 0.8263 - val_loss: 0.3769 - val_accuracy: 0.8648\n","Epoch 2/10\n","1000/1000 [==============================] - 41s 41ms/step - loss: 0.3297 - accuracy: 0.8804 - val_loss: 0.3535 - val_accuracy: 0.8707\n","Epoch 3/10\n","1000/1000 [==============================] - 42s 42ms/step - loss: 0.2903 - accuracy: 0.8942 - val_loss: 0.3153 - val_accuracy: 0.8833\n","Epoch 4/10\n","1000/1000 [==============================] - 42s 42ms/step - loss: 0.2616 - accuracy: 0.9029 - val_loss: 0.2948 - val_accuracy: 0.8928\n","Epoch 5/10\n","1000/1000 [==============================] - 41s 41ms/step - loss: 0.2421 - accuracy: 0.9106 - val_loss: 0.3140 - val_accuracy: 0.8828\n","Epoch 6/10\n","1000/1000 [==============================] - 40s 40ms/step - loss: 0.2242 - accuracy: 0.9166 - val_loss: 0.2746 - val_accuracy: 0.9007\n","Epoch 7/10\n","1000/1000 [==============================] - 39s 39ms/step - loss: 0.2086 - accuracy: 0.9235 - val_loss: 0.2957 - val_accuracy: 0.8916\n","Epoch 8/10\n","1000/1000 [==============================] - 41s 41ms/step - loss: 0.1949 - accuracy: 0.9274 - val_loss: 0.2721 - val_accuracy: 0.9048\n","Epoch 9/10\n","1000/1000 [==============================] - 42s 42ms/step - loss: 0.1820 - accuracy: 0.9317 - val_loss: 0.2921 - val_accuracy: 0.8977\n","Epoch 10/10\n","1000/1000 [==============================] - 39s 39ms/step - loss: 0.1688 - accuracy: 0.9378 - val_loss: 0.2692 - val_accuracy: 0.9062\n"]}]},{"cell_type":"code","source":["plt.plot(history_lenet.history['accuracy'], 'g')\n","plt.plot(history_lenet.history['val_accuracy'], 'r')\n","plt.legend(['accuracy', 'val_accuracy'])\n","plt.title(\"Точность\")\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":452},"id":"LkivY5SP6Ipx","executionInfo":{"status":"ok","timestamp":1719741140940,"user_tz":-180,"elapsed":583,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"fae5cc92-0e72-4281-e4fe-f06e434d2bdd"},"execution_count":156,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["plt.plot(history_lenet.history['loss'], 'm')\n","plt.plot(history_lenet.history['val_loss'], 'b')\n","plt.legend(['loss', 'val_loss'])\n","plt.title(\"Потери\")\n","plt.show()"],"metadata":{"id":"1HKwCXZh6VXy","executionInfo":{"status":"ok","timestamp":1719741144373,"user_tz":-180,"elapsed":461,"user":{"displayName":"Anton Pivnenko","userId":"11044734026939500287"}},"outputId":"9148c48c-140c-4e62-b463-64d3241ccb54","colab":{"base_uri":"https://localhost:8080/","height":452}},"execution_count":157,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["### Какой тип нейросети показал себя лучше?\n","Сверточный НС проявили себя лучше по многим показателям, из недостатков видится только низкая скорость обучения и сложность настройки. Ключевое преимущество заключается в достижении более высоких показателей качества при одновременном снижении значений функции потерь.  \n","На простой модели не удалось достичь 90% качества."],"metadata":{"id":"omN06Q1YYnCv"}},{"cell_type":"markdown","source":["### Какие пробовали настройки и архитектуры?\n","Во время выполнения работы удалось поиграться практически со всеми параметрами (я не торопился и удовлетворял свое любопытство).\n","Из важных наблюдений отмечу:\n","\n","* Большое количество слоев может негативно повлиять на результат.\n","* Параметр batch_size лучше брать кратным количеству данных для обучения. Не понял почему, но результат лучше.\n","* Не существует единого набора параметров, к цели можно прийти разными способами. Например, функция активации tanh проявила себя лучше на небольшом количестве слоев свертки (2 слоя), тогда как relu - показала лучший результат при большем количестве слоев (3 слоя и выше).\n","* Оптимизаторы adam и SGD - показали примерно одинаковый результат, с незначительной разницей в скорости (adam показался быстрее).\n","* Стоит внимательно относиться к входным параметрам. Можно легко запутаться, особенно, если запускать ячейки не последовательно.\n","\n","Из архитектур использовал LeNet в различных конфигурациях."],"metadata":{"id":"r78gf9DvZJ2O"}},{"cell_type":"markdown","source":["### Сложнее ли этот набор данных, чем MNIST?\n","Да сложнее.\n","* Сами данные имеют большее количество признаков.\n","* В MNIST нет необходимости в интерпретации класса.\n","* Много различных артефактов на изображении (эмблемы, складки, затемнения и т.д.), это сбивает с толку даже человека."],"metadata":{"id":"UsiUs7Cfe30v"}}]}